{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This Notebook is accompanied by the following blog-post:\n",
    "http://ataspinar.com/2018/04/04/machine-learning-with-signal-processing-techniques/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from siml.sk_utils import *\n",
    "from siml.signal_analysis_utils import *\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from collections import defaultdict, Counter\n",
    "\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import classification_report"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 0. Loading the signals from file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "activities_description = {\n",
    "    1: 'walking',\n",
    "    2: 'walking upstairs',\n",
    "    3: 'walking downstairs',\n",
    "    4: 'sitting',\n",
    "    5: 'standing',\n",
    "    6: 'laying'\n",
    "}\n",
    "\n",
    "def read_signals(filename):\n",
    "    with open(filename, 'r') as fp:\n",
    "        data = fp.read().splitlines()\n",
    "        data = map(lambda x: x.rstrip().lstrip().split(), data)\n",
    "        data = [list(map(float, line)) for line in data]\n",
    "    return data\n",
    "\n",
    "def read_labels(filename):        \n",
    "    with open(filename, 'r') as fp:\n",
    "        activities = fp.read().splitlines()\n",
    "        activities = list(map(int, activities))\n",
    "    return activities\n",
    "\n",
    "def randomize(dataset, labels):\n",
    "    permutation = np.random.permutation(labels.shape[0])\n",
    "    shuffled_dataset = dataset[permutation, :, :]\n",
    "    shuffled_labels = labels[permutation]\n",
    "    return shuffled_dataset, shuffled_labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The train dataset contains 7352 signals, each one of length 128 and 9 components \n",
      "The test dataset contains 7352 signals, each one of length 128 and 9 components \n",
      "The train dataset contains 7352 labels, with the following distribution:\n",
      " Counter({6: 1407, 5: 1374, 4: 1286, 1: 1226, 2: 1073, 3: 986})\n",
      "The test dataset contains 2947 labels, with the following distribution:\n",
      " Counter({6: 537, 5: 532, 1: 496, 4: 491, 2: 471, 3: 420})\n"
     ]
    }
   ],
   "source": [
    "INPUT_FOLDER_TRAIN = '../datasets/UCI_HAR/train/InertialSignals/'\n",
    "INPUT_FOLDER_TEST = '../datasets/UCI_HAR/test/InertialSignals/'\n",
    "\n",
    "INPUT_FILES_TRAIN = ['body_acc_x_train.txt', 'body_acc_y_train.txt', 'body_acc_z_train.txt', \n",
    "                     'body_gyro_x_train.txt', 'body_gyro_y_train.txt', 'body_gyro_z_train.txt',\n",
    "                     'total_acc_x_train.txt', 'total_acc_y_train.txt', 'total_acc_z_train.txt']\n",
    "\n",
    "INPUT_FILES_TEST = ['body_acc_x_test.txt', 'body_acc_y_test.txt', 'body_acc_z_test.txt', \n",
    "                     'body_gyro_x_test.txt', 'body_gyro_y_test.txt', 'body_gyro_z_test.txt',\n",
    "                     'total_acc_x_test.txt', 'total_acc_y_test.txt', 'total_acc_z_test.txt']\n",
    "\n",
    "LABELFILE_TRAIN = '../datasets/UCI_HAR/train/y_train.txt'\n",
    "LABELFILE_TEST = '../datasets/UCI_HAR/test/y_test.txt'\n",
    "\n",
    "train_signals, test_signals = [], []\n",
    "\n",
    "for input_file in INPUT_FILES_TRAIN:\n",
    "    signal = read_signals(INPUT_FOLDER_TRAIN + input_file)\n",
    "    train_signals.append(signal)\n",
    "train_signals = np.transpose(np.array(train_signals), (1, 2, 0))\n",
    "\n",
    "for input_file in INPUT_FILES_TEST:\n",
    "    signal = read_signals(INPUT_FOLDER_TEST + input_file)\n",
    "    test_signals.append(signal)\n",
    "test_signals = np.transpose(np.array(test_signals), (1, 2, 0))\n",
    "\n",
    "train_labels = read_labels(LABELFILE_TRAIN)\n",
    "test_labels = read_labels(LABELFILE_TEST)\n",
    "\n",
    "[no_signals_train, no_steps_train, no_components_train] = np.shape(train_signals)\n",
    "[no_signals_test, no_steps_test, no_components_test] = np.shape(test_signals)\n",
    "no_labels = len(np.unique(train_labels[:]))\n",
    "\n",
    "print(\"The train dataset contains {} signals, each one of length {} and {} components \".format(no_signals_train, no_steps_train, no_components_train))\n",
    "print(\"The test dataset contains {} signals, each one of length {} and {} components \".format(no_signals_test, no_steps_test, no_components_test))\n",
    "print(\"The train dataset contains {} labels, with the following distribution:\\n {}\".format(np.shape(train_labels)[0], Counter(train_labels[:])))\n",
    "print(\"The test dataset contains {} labels, with the following distribution:\\n {}\".format(np.shape(test_labels)[0], Counter(test_labels[:])))\n",
    "\n",
    "train_signals, train_labels = randomize(train_signals, np.array(train_labels))\n",
    "test_signals, test_labels = randomize(test_signals, np.array(test_labels))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Visualizations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "N = 128\n",
    "f_s = 50\n",
    "t_n = 2.56\n",
    "T = t_n / N\n",
    "sample_rate = 1 / f_s\n",
    "denominator = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "signal_no = 15\n",
    "signals = train_signals[signal_no, :, :]\n",
    "signal = signals[:, 3]\n",
    "label = train_labels[signal_no]\n",
    "activity_name = activities_description[label]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1a. Visualization of the FFT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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FIpaoR9G5c/syx3GcRsGFIoZ06bEuFI7jNBouFDGkCz35dKiO4zQaLhQxeGO24ziOC0Us\nLS3Q1ATNzS4UjuM0Li4UMbS2tjViu1A4jtOouFDEEM5uBy4UjuM0Li4UMbhH4TiO40IRS2urexSO\n4zguFDFEQ08dO9pfFwrHcRoNF4oYoqEnEZ/lznGcxsSFIoaoRwEuFI7jNCYuFDFEPQpwoXAcpzFJ\nLBRiHCIi14rIX0Rk06B8HxHZuHQmVg73KBzHcaA5SSURWQ8YBewGLAK6A38EZgA/AOYDPy6RjRXD\nPQrHcZzkHsU1wCbAEKAnIJFtTwHfKLJdVYF7FI7jOAk9CuBQ4Geq+pKINKVs+wgTkboj2o8CXCgc\nx2lMknoU3YBPMmzrRHsPo27w0JPjOE5yoZgM7J9h2z7AW0lPKCLDRGSyiEwRkeFptp8hIm+JyCQR\nGS8iA5Meu9ikhp46d3ahcByn8UgqFDcA54rIz4H+QVkPETkJOCvYnpUgbHUDcCAwEDgmjRDcp6o7\nqOog4GrguoQ2FpWVK21xj8JxnEYnURuFqv5ZRLYARgCXBsVPAquBq1X1rwnPtyswRVWnAYjI/Vj7\nx7uRcy2K1O8KaMJjF5XoNKghnTr5DHeO4zQeSRuzUdXhInIT8E2gNzAPeDJ86CekL/BxZH0mlnLb\nDhH5EfAToCPw9XQHEpHTgNMA+vfvn65KQURntwtxj8JxnEYksVAAqOoM4LYCzpeu0XsNj0FVbwBu\nEJHvAb8ATkhT51bgVoDBgwcX3euIzpcd4kLhOE4jklEoRCSn13RV/ShBtZm0T6XtB8yKqX8/cFMu\ndhSLTKEnFwrHcRqNOI9iOrm1D6T2r0jHBGArEdkMS7c9GvhetIKIbKWq/w5WDwL+TQXw0JPjOI4R\nJxQn0yYUa2MhoEXAA8BnQB/gSGw4j18nOZmqrhSRs4DHMWG5Q1XfEZFLgYmq+ihwlojsB6wAFpAm\n7FQOMoWewmyo5pyCdo7jOLVLxsedqt4ZfhaR3wOvAYepqkbKLwUewVJdE6Gqo7Bxo6JlF0c+n5P0\nWKUkk0cBsGyZC4XjOI1D0n4UxwC3REUCIFi/mZTwUT2QyaMADz85jtNY5DKER68M23pj/R3qijiP\nwoXCcZxGIqlQjAV+IyK7RAtFZFfg8mB7XeEeheM4jpFUKM4ClgEvi8h0EfmXiEwHXgJag+11Rab0\n2Og2x3GcRiDpEB4fisi2wInA7sBGwNuYUNylqitKZmGF8NCT4ziOkcsQHiuAPwdL3eOhJ8dxHCPx\nnNmNhnsUjuM4RtI5sz8kvpe2quoWxTGpOmhpARHo2LGtrBaEYv58uOIKuPzy9rY7juPkS9LQ0zjW\nFIoNgD2BJcAzxTSqGginQZXIMIa1IBRPPQXXXgtHHgm77JK9vuM4TjaSNmafmK5cRHoAY4CnimhT\nVZA6ux20haGqWSgWL27/13Ecp1AKaqNQ1YXANcDF2erWGqFHEaUWPIolS9r/dRzHKZRiNGa3YsOF\n1xUtLe0bsqFNKKp5lrtQINyjcBynWOQ9tJ2INAPbA5cA7xTLoGqhVj0KDz05jlNskmY9rSZz1tMi\nbN6IuqK1NbNHUc1C4R6F4zjFJqlHcSlrCkUrMAMYrapfFNWqKiBdY3ZzM3ToUN1C4R6F4zjFJmnW\n0yUltqPqaG2FLl3al4lU/yx37lE4jlNsEjVmi8gzwVhP6bZtLSJ1148inUcBtSMUnvXkOE6xSJr1\ntC+wToZt3YF9imJNFZGuMRuqXyg89OQ4TrHJJT02U2P2Fljv7LoiXXosVL9QeOjJcZxik7GNQkRO\nAk4KVhW4VURSHz+dsRTZp0tjXuWoVY/ChcJxnGIT51GsBlYFi6Ssh8s84CbglNKaWX7SpcdC9QuF\nh54cxyk2GT0KVb0LuAtARJ4FzlTV98tlWKXxxmzHcRwjaXrs10ptSDWhCsuW1Z5HsXJlm23uUTiO\nUyzi2iiOB0aq6rzgcyyqendRLasg6ebLDunUCb6o0u6FoRfR3OxC4ThO8YjzKO7E5seeF3yOQ4GG\nEYpq9ShCoejTB2bOhFWroKmpsjY5jlP7xAnFZsCnkc8NQzg6bK2FnkKh2GgjE4olS2DddStrk+M4\ntU9cY/aMdJ8bgTiPonPn6hWKMNy00UZt6y4UjuMUSjHmo6g7QiGoZY8iuu44jlMIcY3ZH5K5N3Yq\nqqpbFMekyhOGnmq1jSLqUTiO4xRKXBvFOJILRV2RzaNoabEUWpHy2pWNUBg23rj9uuM4TiHEtVGc\nWEY7qopsHsXq1dZnYa21ymtXNtyjcBynFHgbRRqypcdG61QT6RqzHcdxCiWxUIjIViJyl4h8ICJL\ng793isiWpTSwEmRLj4XqFIpoPwpwoXAcpzgknTN7X2AU0AKMBD4DNgS+DRwlIsNUdVypjCw3tepR\nLFlis/KFKbGe9eQ4TjFIOmf2b4HXgQNU9T+PHxHpDjwRbB+c5EAiMgy4HmgCblPVK1O2/wQ4FVgJ\nzAVOLnc/jlr1KBYvhm7doGtXa2h3j8JxnGKQNPQ0ELgqKhIAqroYuArYLslBRKQJuAE4MDjmMSIy\nMKXa68BgVd0ReAi4OqGNRaOWPYpu3UwkunVzoXAcpzgkFYqZQMcM2zoCnyQ8zq7AFFWdpqrLgfuB\nQ6MVVPVZVf0yWH0Z6Jfw2EWjloWie3f73L27C4XjOMUhqVBcBYwQkb7RwmD9V8BvEh6nL/BxZH1m\nUJaJU4DR6TaIyGkiMlFEJs6dOzfh6ZORLT0WqlMowtATuFA4jlM8krZR7AN0B6aKyMu0NWbvHnze\nN2jwBuulfUKG46Tropa2U5+IHIu1e+yTbruq3grcCjB48OCidgxsbbU+EulGXq1moViyBNZbzz53\n6+aN2Y7jFIekQjEUm/r0U2DTYIG20WX3itSNe2jPBDaJrPcDZqVWEpH9gJ8D+6jqsoQ2Fo2WlvQN\n2VD9QtG/v312j8JxnGKRdIa7Yg0zPgHYSkQ2w9o1jga+F60gIjsBtwDDVHVOkc6bE62t6cNOUN1C\nkRp6+vjj+PqO4zhJKGvPbFVdCZwFPA68Bzygqu+IyKUickhQ7RqgG/CgiEwSkUfLaSPUtkfhjdmO\n4xSbpKEnAERkEyx0tMb7tqo+k+QYqjoK67wXLbs48nm/XGwqBbXqUYTpseBC4ThO8UjaM3tz4K9Y\neiu0NUpr8FmxDnR1QS0KxbJlsGKFC4XjOMUnqUdxG9AfOBd4H1heMouqgLjQU1hebUIRZjiFoadu\n3ew6fN5sx3EKJalQ7AKcqKp/L6Ux1UKcR7H22m11qonQe4h6FODzZjuOUzi59Myuay8iSpxH0dxs\nS7UJRehRpAqFh58cxymUpELxG+ACEelaSmOqhTiPAtpmuasmUkNPLhSO4xSLpP0o7hGRbYHpQc/s\nBWtWydgbu+aI8yigOufNzhR6cqFwHKdQkmY9nQhciPXO/iprhqHqam7tJB5FtQlFaugp/OvDeDiO\nUyhJG7NHAP8ATlHVhSW0pypoaaldofDQk+M4xSZpG8UGwI2NIBJgIuChp+Lz5ZewsCF+QY5TXyQV\nivHAV0ppSLWgWh+hp2oUirPPhmHDKm2F4zi5kjT0dA7wgIgsAMawZmM2qrq6mIZVihUrYPXq2vMo\nliyxme26dLH1ahSKSZPg3XdNjCXdgPOO41QlSYXiveDv3TF16qL/b9zsdiGdOsHSpeWxJynhyLHh\nA7hLl+qbN3vaNLu/s2fDRhtV2hrHcZKSVCgupc4ymzIR9o/I5lHMm1cee5ISHRAQ2ubNrpaspwUL\n2tonpk1zoXCcWiJpP4pLMm0LZrY7vkj2VJykHkU1hp7CcFNINQ0MOG1a+89DhlTOFsdxciOv+ShE\nZMtgDokPgaeBI4trVuWImy87pBqFIjppUUg1C4XjOLVDYqEQkXVF5DQRGQ9MxqYqXQD8ENi4RPaV\nnVAAarExu5qFYupU+7v++i4UjlNrxAqFiHQQkW+JyP3Y/Ng3AwOAG4Iq56rqLaq6qLRmlg8PPZWG\nadOgd2/YYQcXCsepNTIKhYhci81r/U/g21jP7GHYvBQX0zZ5UV2RtDG72oSiFkJPm29uiwuF49QW\ncY3ZP8EynUZhc1H8J89HROo2AyoXj6Ka+gOk8yiqKetp2jTYYw8Tilmzsg+86DhO9RAXeroDWAwc\nBEwWkT+JyK4x9euCJB5F584mEitWlMemJFSzR7FiBXz0UZtHATB9ekVNchwnBzIKhaqeCvQBjgVe\nBc4AXhKR94ALqNN+FUk9imjdSqNa3Y3ZH31kU7JusUWbUHj4yXFqh9jGbFVtVdX7VPUAYBPgImyo\n8eFYG8WVInKsiMQ8VmuLpOmxUD1C0dJiYpGuMbulBVaurIxdIaEoRD0KFwrHqR0Sp8eq6qeqepWq\nbg/sBtwIbIUN6/FpiewrO0nTY6F6ZrlLHTk2JDpvdiWJCkWvXtC1qwuF49QSeXW4U9UJqnoW1n/i\ncGBcUa2qILUYekodOTakmoSiY0fYeGNr/PfMJ8epLZKO9ZQWVV0BPBwsdUHS9FioPqFIl/UElW+n\nmDYNNtsMOgSvJZtt5kLhOLVEXh5FPdPaag+05hgJrTahyBZ6qgahCNsmoM2j0LpMh3Cc+sOFIoUw\nvz+uf0S1CUW20FMlhULVhu/YYou2ss03t9nu5sypnF2O4yTHhSKFbLPbQfUKRbqsJ6isUCxYAF98\nsaZHAR5+cpxawYUihZaW2hOKag49RTOeQlwoHKe2cKFIYf58G+E0jmoTikyhp3C9kllP6YRiwID2\n2xzHqW5cKFKYPRv69ImvU61CUY2hp1AMNtusraxzZ0uVdaFwnNrAhSKFTz+tPaFYvNiytDp2bF/e\npYtlcFVSKKZOteHFU70d70vhOLWDC0UE1dr1KLp1WzNTK5w3u9IeRTTjKcSFwnFqBxeKCAsXwvLl\nsNFG8fWqTSgWL14z7BRS6YEBU/tQhGy+OXzySfXcQ8dxMlN2oRCRYSIyWUSmiMjwNNv3FpHXRGSl\niBxeTttmz7a/2TyKtde2v9XykEs3cmxI9+7pG7MXLYLPPiutXdHhxVPZfHPz4GbMKK0NjuMUTlmF\nQkSasGlUDwQGAseIyMCUah8BJwL3ldM2sPYJyC4UTU3WHrB0aeltSkKcUGQKPZ11Fuy/f2nt+ugj\nWL06s1CAh58cpxYot0exKzBFVaep6nLgfuDQaAVVna6qbwKry2xbYo8CYNNNq2fynXxCTy+9BO+8\nY6G2QlGFuXPXLE+XGhviQuE4tUO5haIv8HFkfWZQljMicpqITBSRiXPTPaXyIBSKbG0UANtuC++/\nX5TTFky20FOqUCxeDFOm2GRCU6cWfv6RI01cx45tXx4eO51Q9OljbT0uFI5T/ZRbKNKNoJTX0HCq\nequqDlbVwb169SrQLGP2bGt/WHfd7HW32QY++MAetpUm3XzZIemE4q232j5Pnlz4+UePthDT2We3\nnx522jS7nxtvvOY+Pty449QO5RaKmdhMeSH9gFlltiEjYWps3ICAIdtuC8uWVUdjbLr5skPSCcUb\nb7R9LoZQjB1rfSXefhtuvLGtPHV48VRcKBynNii3UEwAthKRzUSkI3A08GiZbchIks52Idtua3+r\nIfyUa9bTpEmw3nqw4YaFC8WcOfDuu3DuudY4fvHFbdlUmVJjQ4o93PjIkXDEET58ueMUm7IKhaqu\nBM4CHgfeAx5Q1XdE5FIROQRARHYRkZnAEcAtIvJOueybPTtZ+wRUj1CsWmVDdmcKPXXrtua82W+8\nAf/1XxY+K1QonnvO/u67L/zhD3auCy9sG148m1AsWQKff16YDSF/+Qs89FBbW5PjOMWh7P0oVHWU\nqm6tqluo6uVB2cWq+mjweYKq9lPVrqq6gapuVy7bkvTKDtlgA+jZszhCcdFFsPfe+e0bpujGeRTQ\n5lWsWgVvvlk8oRg3zoYKGTzYjnfuufbAHjPG+mpkEwooTvhJFcaPt8/vvlv48RzHacN7ZgesWGFv\ntkmFAoqX+fT887bk096RaeTYkNSBAadMsbf+QYPswT5vni35MnYsDB0Ka61l67/8pXllJ5xg6+US\nimnT2kJeLhSOU1xcKALCh0yuQlGMxuAwjXTMmNz3zTRybEiqUEyaZH9DjwIseysfPv/cGrD32af9\n+a65pq1fRbpxnkLCEWWLIRQvvGB/O3RwoXCcYuNCEZBLH4qQbbe1xtz58/M/75dftvUIHz069/0z\nTVoUkioUb7xhI80OHNgmFPmHXE6AAAAZdUlEQVSKXbR9Isr3vmdehkj74cVT6dLFhLkYD/bx46FH\nD9htNxcKxyk2LhQBufTKDgkbtAvxKsK36d694emnc+8pnTT0FNabNAm+8hXr3zBggIlGvvaPHWtz\nSwwe3L5cBP72N3jgAejaNf4YhxwC998PL7+cnw0hL7wAe+4J22/vQuE4xcaFIiAfoQjfyAtppwjD\nTqedZg/zMISSlNBTiMt6itZ74w1rnwBrV9hii/yFYtw4GDJkzXkwAPr1g8MTDOl4zTWwySZw3HH5\nj501f76Jw5Ah5il9/nn6IUUcx8kPF4qAMPyz4YbJ9xkwwB6ShQjFlCn29wc/sAd3ruGnXBqz586F\nWbOsfSIk38ynefMseyo17JQr66wDd91lgnn++fkd48UX7e/QoeYtgXsVjlNMXCgCZs+2ubLDIcST\n0NwMW21VuEfRowf07w977ZV7g3YuQhH2yA49CjChCMd9yoWwfSLakJ0v++wD550HN90Ejz+e+/4v\nvGAiu8su5lGAC4XjFBMXioBc+lBEKTRFdurUtsygYcNsHKaZM5Pvny30lE4oUj2K5ctzT80dN87a\nJ3bZJbf9MnH55bDddnDSSbknB4wfD1/9qtnTr5+J5nvvFccux3FcKP5DIUIxdWr+w3VHheLAA+1v\nLl5F6FFkajTu3NlSRpcssYbsvn2to2BIvplPY8fCHnvk5oHF0akT3HOPhcd+9KPk+y1bBhMmWNgJ\nrCF94ED3KBynmLhQBOQyzlOUbbfNf7julSvtTT4Uiu22szfiXIVi7bXbOrylEp03Oxy6I0o+QjF/\nfnHaJ1LZaSe45BLLgnrkkWT7vPqqicWQIW1lLhSOU1xcKLDhH3IZ5ylKIWM+ffSRicWWW9q6iIWf\nnnyy/XDdccRNWhTSvbtlAr33Xvv2CTDvokeP3ITi+eftnhVbKAAuuMBseuyxZPXDLLFUofj0U1iw\noPj2OU4j4kKBPWxbWvLzKApJkQ29kGjv5QMPtDGSXnop2THiRo4N6d4d/vUvE6VUj0Ik98ynsWMt\nVLTrrsn3SUpzs4lZ2IM8Gy+8YAkFvXu3lYUN2t5O4TjFwYWC/PpQhHTvbnH/fIQiTI2NCsV++9nD\nMmmabFKhCM+VKhSQu1CMG1fc9olUBg2yoUGyeVWqJhRRbwI888lxik1zpQ2oBsI+FPmEniD/zKep\nU9ecAW6ddezBN2YMXHFF9mMkDT2BDZkRhrmibLMN3H13+mM995x5I/PnWyhnwQJ727/kkuy25cug\nQdbuMHmy9bTOxAcfWEgtbMgO2XRTa8R3oXCc4uBCQWEeBdiD9q9/tTfcJLPjhYTzNaTOADdsmM3p\n8Omn2cUrbhrUkHD7DjtAU1N6+wH+/W9LMw157z1rh1A1L2e99WwZOhSOOir+nIUQtqNMmhQvFOGw\n4qkeRYcOJt4uFI5THDz0ROFCse228MUXbSPQJiWaGhsllzTZJEIRhqZSG7JDMmU+XXGFvZl//LGl\n/86ZY3Wee65tn1KwzTbmaUWnbE3HCy/YvCDpbPHMJ8cpHi4UmFCstZb1zM6HfDKfVG1AwHRCseOO\nFo566KHsx4mbLzskFJJ07RNg4SiR9kIxdSrcdx+ccYal7ObiKRVKc7N5EtkatMP2iXS2DRxoArdo\nUWlsdJxGwoWCtj4U+T4M8xGKzz6zQfDSCYUI/PCHMGqUpaLGkbQxGzJ7FJ062bhVUaG46ip7YP/0\np/HHLhVh5lOm+a/nzLE2itSwU0jYoF3pqWodpx5woSD/Xtkhfftaz+hcHkphamy6xmWwsY/69oWf\n/SzzwxKShZ422sjEYIcdMtfZeus2ofj4Y7jzTjjllPYN7eVk0CBrqJ41K/32TO0TIZ4i6zjFw4WC\nwoWiQweLk+cjFJlmgOvSBS67DF55xeZ1SMeKFZYdlM2jOP10i/fH1dtmG3tDV7Whv1Xhf/4n+3WU\nimiDdjqeeMIEMtNYU5tvbiP7ejuF4xSOCwWFCwXkniI7ZYoJzIABmescd5y1KwwfboKQSraRY0O6\ndDGPIY5ttrFQ2GuvwZ//DMcfb2mmlWLHHe1vugZtVWvo/8Y30s+FARY222YbFwrHKQYNLxSrVtlA\ndPn2oQjZdlsbt+nLL5PVnzrVJuzJ9KADS2W99lqYPh3+9Kc1t4fZWtlCT0kIM4fOPNMynIYPL/yY\nhbDOOuYVpPMo3n/f7vWwYfHH8MwnxykODS8Uc+bA6tXF8SjAwjdJyJQam8p++1m67GWXtR9+++GH\nbR6Hjh3XnIo0H0KhmDABjj7ahsWoNJmG8gjThpMIxYcfJhdvx3HS0/BCUWgfipBwZrU99zQBGDoU\njjjCejCnCxslFQqAq6+2NM9QLL7/ffjud22yo9dey5z2mgthgzzARRcVfrxiMGiQhejCOTdCxoyx\n+50tNDZwoIWpCpnT3HEcF4qiCcV228Gtt1roZvfd7U3/rbdgxAi4/fb2dRctsoyepEKx/fZw8skW\nftp+e2vcHjHCBg7cbrvC7A4RMXE77rjiHbNQBg2yB/1bb7WVffmljTWVzZuA2psWdeVK+Pvf3QNy\nqo+GH8IjFIpC2yhEbN7rKKo2eN5111nmUTh8RrbU2HRceik8+KD1RB450uZuKDajR8en4pabaObT\nnnva57FjzUMLe6/HsdVWds9DoVi92kTnxRdNzEtxDwvh9tutg+Mpp8Btt1XaGsdpo+E9inBAwA03\nLP6xRawfxNSp8OijbeXZUmPTsdFG1pP7tddK94ATWXPcqUrSr5+NLRXNfBo92oYV2Wuv7Pt37Ghi\n8Y9/wMEHm8gOGmSdGQ891LK8cuGLL+z+5yqmy5fD4YfDlVdmrrNsmU0H26mTCcbIkbmdw3FKSRU9\nFirD7Nmw7rr28CkFhx0Gm21m2Ush6YYXT8L662eeya4eEVmzQXvMGPja1+yBmoTddrNOd1OnWpvR\n3Xfb0Cgff2wP5iS8846JS9++sPPOcOyxuYWHLrjAQkq/+IXNDJiO2283mx580FKDTz0V5s1Lfo5G\n4c0324cinTKhqjW/7LzzzpovRxyhus02ee+eiD/8QRVUX3rJ1k89VbVXr9Kes1447zzVTp1UV6xQ\n/fe/7T7+8Y/J91+2THXevDXLjz9eda21VCdPTr/f6tWqDz+suu++ds6111Y98UTVCy9UFVH9r/9S\nnTYt+/kffND2P/lk1Z49VYcMUV21qn2dlhbVvn1Vhw61806aZLYdeWTy66wWPv9cdfbs4h935UrV\nyy9XbWpSXXdd1Q8/LP45GhFgoiZ4xlb8IV+MpRCh2GsvexiUksWLVXv0UD38cFv/2tdUd9+9tOes\nF+66y36l775rAgEmGIUye7bqOuuo7r+/PZyjrF6tesEFdq5NN1W96irVuXPbto8ebd/n+uurPvFE\n5nNMnqzavbt918uWqd5+ux3zL39pXy98kXj66bayyy+3svvvL/RK21i6VPWFF+whm3rNxeDhh1W7\ndDG7t95a9ZRT7Psr9KE+a5b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UH8RmRRuBpa3uHqm3XES+CVwInAkMwMJAU4BRZG67iONI\nYDgWVvoJ8AU2Q9vsFBtfF5FpwBxVfTOP8+TLBkCvYHkxZdtUTCSdBsBnuHMaChGZCYxR1VMrbUtS\nRGQg9lZ/kqrelXCf8VgD+gHAalXNN9srybmasJfOVmCEql5SqnM5lcHTYx2nShGRfsHgfbdg/ULu\nz/EQX8c8nVuLbFoqUzGRcOoUDz05TvVyBhbqmgwck0sbCNam0T34PLfYhqXwbWDt4POsEp/LqQAe\nenIcx3Fi8dCT4ziOE4sLheM4jhOLC4XjOI4TiwuF4ziOE4sLheM4jhPL/wM235xab1iDSAAAAABJ\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f05d56c2d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f_values, fft_values = get_fft_values(signal, T, N, f_s)\n",
    "\n",
    "plt.plot(f_values, fft_values, linestyle='-', color='blue')\n",
    "plt.xlabel('Frequency [Hz]', fontsize=16)\n",
    "plt.ylabel('Amplitude', fontsize=16)\n",
    "plt.title(\"Frequency domain of the signal\", fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1b. Visualization of the PSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ataspinar/anaconda3/lib/python3.6/site-packages/scipy/signal/spectral.py:1633: UserWarning: nperseg = 256 is greater than input length  = 128, using nperseg = 128\n",
      "  .format(nperseg, input_length))\n"
     ]
    },
    {
     "data": {
      "image/png": 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tzVuPPgrvehfMnAnf+hZ85CNpav0FCyofa2a1cSCpwiWXwH/9VwomJ59c+/H1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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f05d56c2358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f_values, psd_values = get_psd_values(signal, T, N, f_s)\n",
    " \n",
    "plt.plot(f_values, psd_values, linestyle='-', color='blue')\n",
    "plt.xlabel('Frequency [Hz]')\n",
    "plt.ylabel('PSD [V**2 / Hz]')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1c. Visualization of the Autocorrelation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MruP3uWQ+44Tvt6Cfcbm0KPYC3nT3t919FXAXcESNc44Absv8fB8w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\nRESyUqIQEZGs/j9n9M7wQHY2/gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f05d56c2630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t_values, autocorr_values = get_autocorr_values(signal, T, N, f_s)\n",
    " \n",
    "plt.plot(t_values, autocorr_values, linestyle='-', color='blue')\n",
    "plt.xlabel('time delay [s]')\n",
    "plt.ylabel('Autocorrelation amplitude')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1d. Visualization of all transformations on all components"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ataspinar/anaconda3/lib/python3.6/site-packages/scipy/signal/spectral.py:1633: UserWarning: nperseg = 256 is greater than input length  = 128, using nperseg = 128\n",
      "  .format(nperseg, input_length))\n"
     ]
    },
    {
     "data": {
      "image/png": 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eQdsvLVFvbSfnXGnTGf7s2fOgeFMNoZmQi0XHxbvuUY75ItpJOFJEbkPDly9B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\nxC5cdLz55pvZ8+fPz2t7zcsL7SK7qqrOU1X1xSaP11RV/VJV1bKLfZA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T0GvX3x+mTZO2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WfyOgbDeYLRKxi9YjCcZoxewegVg6EgJozZcEoopXr7wmSuV0p96lOs+wocb/f/7N15fJXV\nvff9z2/vnYkMjAFkDELCkEDVKCqCoh4VK0f0VMTjqa3a3mrPo7a16m2fVkWOdtBbz1Ha42ytPU7V\nPrUqOODEjVqrgVoBiSKKAoIyZw7ZyXr+uK4NO8neyd4ZyPR9v177lb2vaa9EWdf6Xeu31jKz58xs\nj5lVm9mbZnZcjOv82Mw+N7MaM3vXzGb4aT0PHKTf439aSIGaeTDKICIe1Ssi0tFUr4j0TQp2JRFB\nMwtFvYIxjvktEAb+DfgegJkdBbwF9Ae+D5wD7AVeNbPDIiea2aXAHcAyYB7wP8CTQE4HlN2alD1k\nZiHAmhx3I3Bsk9c7QAWwqQPKISKNqV4RkY6mekVEGlEasySitMnnt4CmTw/fds5d0mTb/wE+BU52\nztUBmNlLeONnfg6c49+IbgCWOOe+75/3kpntxLuJtNd3/Fcs9ZE3zrkNwIbIZzO7DpgOnOWc+7wD\nyiEijaleEZGOpnpFRBpRsCuJOJvGEz6Uxzjmz9EfzCwT7wZzE+D8p5MRrwLf8t+PBUYAP21yvaeA\nR9pR5ojn/TI0dTnw7VgnmNnZwC+Aq5xzz3VAGUSkOdUrItLRVK+ISCMKdiURaxKY8GFrk89D8NLk\nbyJ25d3g/zzE//lV9E7n3D4z251sQWPY6ZwrabrRzLbFOtjMDgf+ANzjnPuvDvh+EYlN9YqIdDTV\nKyLSiIJd6Siuyefd/rY7gUdbOC9y0xkWvdHMUoGBHVa6BJjZIcBzwJvAlQfzu0UkJtUrItLRVK+I\n9CEKdqVTOOfKzOxtYBpeek3Tm0vE58CXwLk0TgOaz0GcQM3MMoBngT3Auc65pBZwF5HOp3pFRDqa\n6hWR3k3BrnSmHwNvAC+a2UPANrx0oSMB55z7f51z9Wa2CLjHn7b/KaAAuJbYY206y2K8G913gSlm\njSY/XOucO5hlEZH4VK+ISEdTvSLSSynYlU7jnHvPzKbjTZP/G7wp/b8CVgL3RB13rz9BxI/wJmFY\nDSwA/ngQizsJSAUej7FvFl6qkIh0MdUrItLRVK+I9F4WP1tDpGuZ2Wbgxagp/mMd833gfiAP2Oyc\nq493bAeUJ4CXqvR74DjnXF5nfZeIdA7VKyLS0VSviHRfB22MgUgn2wjUdvJ33ADUAed38veISPew\nEdUrItKxNqJ6ReSgURqz9HTPAO/77zs7TeE+vHXwoPNvVCLSdVSviEhHU70i0gWUxiwiIiIiIiK9\njtKYRUREREREpNdRsCsiIiIiIiK9joJdERERERER6XUU7IqIiIiIiEivo2BXREREREREeh0FuyIi\nIiIiItLrKNgVERERERGRXkfBroiIiIiIiPQ6CnZFRERERESk11GwKyIiIiIiIr2Ogl0RERERERHp\ndRTsioiIiIiISK+jYFdERERERER6HQW7IiIiIiIi0uso2BUREREREZFeR8GuiIiIiIiI9DoKdkVE\nRERERKTXUbArIiIiIiIivY6CXREREREREel1FOyKiIiIiIhIr6NgV0RERERERHodBbuSFDO70Mxc\n1KvczP5hZpebWSjquBwzu8nMPjSzSjPbbWarzexeMxsaddzDUddqMLO9/jkPmtmxXfNbikhnUj0i\nItG6Y51gZoeZ2UIzG9TG36m95+f55b+wLeeLiCfU+iEiMc0HNgM5/vvFwFDgBjMLAq8AecCvgfeB\nTKAI+FdgBPB11LW2A2f67zOBicC3gbfN7FfOuZ929i8jIl1C9YiIROtOdcJhwI3A/wC72vC7tPd8\nEekACnalrd53zn3iv3/ZzCYAPwJuAE4AjgLOcs79JeqcZ4FfmFnTjIJ9zrl3oj6/amZ3A/8JXGdm\nJc65P3XOryEiXahP1SNmluacq+3KMoh0c32qThCRzqc0Zuko7wHZfhpRJGVnW6wDnXMNrV3MOeeA\na4Gv8G50cZlZupn9p5mtMbMKM9tmZs+Z2aQYx44zsz/4x9Sa2admdmeTY04ws2V+2lOln0r1vdbK\nLCLt1mX1CICZHWFmK8ysxsw2mdn/66dMuqhjVpvZn2OcO9tPOTzN/7zQ/1xkZi+ZWQXwR3+fmdmP\nzewjM9tnZlvN7DdmltNaGUX6mC6pE/zU4d/5H9dHpUTn+ftz/H+zX/ptiY/8f9OW4PmXm9lfzWyX\nme0xs3fM7IzWyh+nrBP8ds1nZlbtt2vuNrOBMY5ttX1jZv/LzFb519ptZsvNbEZbyibSHSjYlY4y\nDqgHKoBVQBi418zOjlXhJsI5tw94FZhuUWN2YkgDsoGbgTOAHwDpwDtmNjxykJmNA94FjsdLLTod\nuAkYEnXMPP87U4FLgXnAQ8DYtvwOIpKULqtHzGyIf9wg4DvAFcBpwIVNDr0bmGtmI5psvxT4DHi5\nyfa/AMvx0in/0992C3AHsAz4Z+BW/3uWxOidEunLuqpOWILXpgAvnfpY/7XV/ze6BLgIuB3v3/CL\neP+mb2ntfH9bHvCAv28BUAI8b2ant+FXGoGX+v0jvDprEXAysDT6oETaN2b2f4D78P7W5+Klff9f\nYEwbyiXSPTjn9NIr4Rdeg8zhjX0JAQPxKs164Jmo476Pd3NyQAOwFrgNGNHkeg8Dm1v4vl/61xiW\nRBmDQD+gHPhx1PZH/DKNiHOeARvxbjqBrv5b66VXb311x3oE+AWwDxgVtS0DrwfIRW3LBsqA66O2\nDQFqgeuiti30v/OHTb5nEFADPNxk+7f948/s6v8+eul1sF/dtE6IlGlCk+1z/e0XNtn+gF8PDGnp\n/BjfE/B/55eBv0Rtz4v1PQn8LUPATP/cw/1trbZvgAn+3/uOrv7/QS+9OvKlJ8jSVqVAHd6kC/8N\nPApcHNnpnHsAGI3XgLsPrzK/GlhrZoVJfI9FLtniQWbnmtnfzGwP3pPfSiAL78YZcSrwvHPuyziX\nmYj3hPMBl0A6lIi0W3eqR44B/uqc2xz1/dV4PTREbSvHm3Dm+1G9sBf53/E7mmua8nwMXjbK/zTZ\n/gRe3XVCC2UU6e26U50Qz/F4gfbjTbb/D16vaauzPZtZsZk9b2Zf4f27rwNOoXGbJSFmluoPuSg1\ns2r/Wiv83ROjfrbWvvknvL/nfcmWQaQ7U7ArbXU23kQRk4BM59x3nHONZht0zu12zj3qnLvMOTcZ\nOAtvhsWbkvie0Xi9LXFnMjSzfwaeBNYB5wNH+2XbjpfOHDEYL9UnnsH+z5aOEZGO023qEeAQGs/k\nGvFVjG3/jZfW901/jN4lwJ+dc7GO3drk86BY251zYWBn1H6Rvqg71QnxDAJ2ueaTzW2L2h+XmY3m\nwJCJK4AZeL/zizRusyTql3iZJP+DN5RrOvAv/r7I9RJp36gNJL2SZmOWtlrjDsyYmBDn3F/M7B/A\nlESON7NUvCeN7/gNwXjOAz5xzl0YdW4KzW84O4CRLVxnh/+zpWNEpON0p3pkK94SJ00Ni1GGNWa2\nAi/NsgYv/e/SeEVu8jnSuB6Ol4IZKWcIr7G5s4UyivR23alOiGcXMMjMUp03/jciMkdIa/+G5wD9\ngXOjM0nMrF8bygJeG+gR51xkjDBmltXkmETaN9HHfNTGsoh0O+rZlQ5nZkPMrNnTSTPLxHua2rSn\nI9Y1DG/SlqEcmNQlnn54aUDRLsAbuxvtZbyJZQ6Jc52P8ca0fD8yo6KIdI0uqEfeAY41s1FR52fg\n9ZTE8t94k9wtBD52zr3WWnmivqcWr4EabQHeA+jlCV5HpE/pgjoh0nOb0WT7crz28/wm2/8Nr7c4\nstxRvPMjQW1dVLkKgONaKU88/aKv5buoyedE2jev4KVnX9LGcoh0S+rZlc4wG7jbzB7GGzeyB2+s\nyBV4va13NDk+1cyO8d/348DC78cCNzvnnmnl+14EzjKz/wSeB4qBK/3vjXYjXsP1bTP7BfAJ3hPM\nOc65bzvnnJn9CPj/gNfM7B68VOjJwFDn3I2J/wlEpJ1mc3DrkTvwZnJ/ycxuwmuoXuX/jDWu70/A\nf+E1UH+S6C/lnNtlZncAPzWzSrwZUyfjzdz6Jk3GCIvIfrM5uHXCh/7P/8fMfo8XUH4AvID3b/Ue\nM8vFy9D4Jt7kWb90zu1o5fxX8B7QP2Jmt+MNobgJ+IK2dUK9CHzXzFbjtWv+BS81er9E2jfOuQ1+\nO+oqM8vGW7+4Hi8tutQ592QbyibS9bp6hiy9etaLBGYXBEbhjSH5G94YuDq8SnUpcFKTYx/2rxeZ\nWbEcb+ztg8AxCZYpgNdQ/BKownvqejjeU8yHmxw7Hm9SiR14jdhPgf9scsxJwOt4Mz5WAP8ALurq\nv71eevWWV3esR/zrHIHXiK0BtgDXA3cCu+Mcf69/7OAY+xb65QnF2GfAj/FSBffh9Uj9Fsjp6v82\neunVFa9uXCfc6NcF9f618vztOcBv/H+7+/B6Tn8MWILnn4s3GVcNXrB8nl/mjVHn5pHAbMx4s8E/\nAez2X4/ijQGONWN0q+0b4DK8oLwWL2X7DeDYrv5/RC+92voy59oyEZ2IiEjvZmZBvPUmdzjnTm6y\nL4TXi7LCOXdBV5RPREREWqY0ZhEREcDM/gMvgP0cb7Ko7wPT8FIUI8fkAEV4M7+PBm4/+CUVERGR\nRCjYFRER8TjgBmCE//4D4Czn3AtRxxyBlwb4NfBD59z7B72UIiIikhClMYuIiIiIiEivo6WHRERE\nREREpNfpE2nMQ4YMcXl5eV1dDBHxrVy5codzLrery9EeqldEuhfVKyLS0XpDvdLX9YlgNy8vj5KS\nkq4uhoj4zOzzri5De6leEeleVK+ISEfrDfVKX6c0ZhEREREREel1FOyKiIiIiIhIr6NgV0RERERE\nRHodBbvtVV0Nc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/YmmGm09FCKFzBr3K6IxFVdTaX/cD41mMqYwEA2DCKhJc9EpPtZvnx5\nv4KCgilVVVVWVlYWmDBhQuF7772XHn3Mpk2bQqeccsr4iRMnTpk4ceKUZcuWZQIsXLhwWH5+fmF+\nfn7hokWLhgJ89NFHqePGjStcsGDB2Pz8/MIzzzxz3DPPPJN9xBFHTBo7dmzR66+/3g/gqquuGnHW\nWWeNO+aYYwrGjh1bdPvttw8BaGho4NJLLx2Vn59fWFBQMOX+++8fCPD8889nT58+feKcOXMOHTdu\nXOGZZ545rqHBezi/YsWKfkcdddTEwsLCyTNnzsz//PPPUwCmT58+8Qc/+MHIqVOnTs7Lyyt68cUX\ns2pqauyXv/zliOeee27gpEmT9l8/UcmmMS+n+RJBg4EZQAXwWpLX67kiPbtBr7E5PpjLJ4M2eTeP\nFsbdiYjEDHYT6NlNDaYSsAPPKDNCXv1TXVdNv5R+nVJUEenh/PZKZtCrc8anDWfDwF3eChKDBnVx\n4UR6uIsvHs2aNR17Ay4qquKhhzbF233CCSdUzZkzZ8+PfvSjkdXV1YH58+fvPOqooxo99b7sssvG\nzJo1q/yGG27YEA6H2bt3b3DFihX9HnvsscErV65c55yjuLh48sknn1w+ZMiQ+k2bNqU/+eSTnxYX\nF38+bdq0yY8++ujgkpKS0scee2zALbfccsiJJ564AWDdunUZK1euXFdeXh48/PDDp3zrW9/a+8Yb\nb2SuXr06Y926dWu3bt0amj59+uRTTz21InL8+++//2leXl5dcXHxpGXLlmXNnj278sorrxyzZMmS\nT0aMGBG+//77B1599dUjn3rqqY0A4XDYVq9eve7JJ5/sv2jRohFz5sz5+Kc//emXJSUlmY888sgX\nyf45k52g6sJY2/0Zkl8EXkm2AD2WPwYmK8VbWnhC+kjeHbjJu3ko2BWRlrQx2I1OYYYDPbuapEpE\n4qqpoTIFsoJee3xC5mieHvShlksU6cFuvfXWrd/4xjcmp6WlNfzud79rFgC+/fbb2U8//fRnAKFQ\niMGDB9e/8cYbWd/85jf35OTkNACcccYZu19//fXs+fPn7xk5cmTt9OnTqwEKCgqqTzrppLJAIMAR\nRxxRdfPNN4+IXPf000/fk5WV5bKyssLHHnts2YoVKzJXrFiRfe655+4KhUKMHj06fPTRR1e8+eab\n/fr3798wderUyvHjx9cBFBYWVm3YsCF10KBB4fXr12ecdNJJBeD1DOfm5u6f5Hj+/Pm7AWbMmFF5\nzTXXpLb3b5X0BFWxOOf2mNlteGvtPtYR1+z2/KWHIsHu+OwxPDXgHep2bidlwoQuLpyIdGttDHaj\nJ6eCxj27IiIxRR7Oh7xgd/yAQ9m5E/Zs38QAjuziwon0cC30wHamr7/+OlhVVRUIh8NWVVUV+NnP\nfnbIsmXL+gOUlpZ+GOsc5+KvlpSamrp/ZyAQID093QEEg0Hq6+stss/MGp1nZi1eNy0tbf/OYDBI\nOBw255xNmDCh+v333y+NdU7ku0OhUKPvbquOnKCqBhjVgdfr3iJpQal+sDtoPPUB+HxbzP9uIiIH\nRAe7oRBkZrY6ZremXj27ItIGkfaKP9RhfG4BABu+/qgrSyUi7XDhhRfm/exnP/vynHPO2Xn55ZeP\nWrx48ZbS0tIPI4HucccdV37bbbflAoTDYXbt2hU46aSTKpYuXTqgvLw8UFZWFli6dOnAE088ManZ\ndV944YUBVVVVtm3btuA777yTPXPmzMoTTjih/Omnnx4UDof58ssvQ++++27WrFmzKuNdY9q0aTW7\ndu0KvfLKK5kAtbW1VlJSkh7veICcnJz6ioqKNsWt7Q52zSxkZocBC4G17b1ejxF5UpqaDcCEoZMB\n2LBjfVeWSqRPM7M5ZvaRmX1iZtfF2H+8ma0ys7CZndNk33fNbL3/+m6nFjQ62AWvd7eVnt3acG3z\nYDekCapEpBWRTLTULADGH1IIwIbdfWdOUZHe5De/+c3gUCjkLrvssl233HLLtvfff7/fs88+mx19\nzN133/3F8uXLswsKCqYUFRVNWbVqVcbMmTOrzj///J1HHHHE5OLi4skXXHDB9uOOOy6pp+WHH354\n5cknn5x/9NFHT7766qu35uXl1V1wwQV7CgsLqydPnlw4e/bsgptuumnzmDFj4s7Ym56e7p544okN\n11133aiJEydOKSwsnLJ8+fKslr739NNPL//4448zOn2CKjNroPkEVRFlwBnJXK9Hi0xQlZ4DwPiR\n3gq7G/Z+1pWlEumzzCwI/BY4BdgMvGdmzzrnotN5vgAuBK5ucu4g4EbgSLw6bqV/bucMaqupObDk\nEHjv2zNmV2nMIhKP/3A+kol26Bh/rd2KLsm+FJF2uvzyy3defvnlO8FL9f3ggw+apZWOHj06/Oqr\nrzZ7orVw4cKvFi5c+FX0tokTJ+5bv379/g7LP/3pTxvj7cvPz695/PHHP48+PxAIcO+9927Ga3vt\nN3fu3PK5c+fu7zmOnlxqxowZ1SUlJc3SS95999392w455JDwli1bVgMMGzasfs2aNeuaHp+IZMfs\nLqJ5sFsDfA684JzrO/PY+0sPRYLdQ0ZOIqMOPqnUzUOki0wHPnHOfQpgZk8A84D9wa5zbqO/r+nC\ntKcBy5xzu/z9y4A5wOOdUtLqahg+/MDn/v1bT2OOFeyGlMYsIq2IPJxP89or2f2HMrQSNqR92cUF\nExHpfMnOxrywk8rR49RXV1GVCpkZ3s3DMjI4dI+xYeBXrZwpIp1kJBD9tGkzcHQ7zh3ZQeVqLlYa\n844dLZ8Srmm0xi6wP/hVz66IxNXk4TxmjC9PYUOo5TpHRCTaHXfc0SOfkCU1ZtfMXjOzSXH2FZhZ\nn1lnt6rG65XP6ncgFXFMdSqbGzSVv0gXiTVjX/wpAttwrpldYmYlZlayffv2pArXSNNgt71pzOrZ\nFZE4XHU1lVEP5wHG1KazmaTmpRER6ZGSnaBqNpATZ182cEK7StODVNaUAVFPSoH+pFHuaruqSCJ9\n3WZgdNTnUUCiTyETOtc5d59z7kjn3JG5ubltLmjMnt1W0phr6+NPUKWeXRGJp7qmHGeQldF//7ac\nQAbltq8LSyUicnC0ZTbmeD0l44GKdpSlR6mo9Z6IZqYemDwsJ5BBmW4eIl3lPSDfzMaZWSpwHvBs\ngue+BJxqZgPNbCBwqr+tc7RhNmb17IpIW1TUeHVLZlQmWk4ok/JA3MlSRUR6jVbH7JrZRcBF/kcH\n3GdmTXNfMoAi4NWOLV73VbHPi+uzooPdtBzKAl93VZFE+jTnXNjMLscLUoPAQ865tWa2CChxzj1r\nZkcBfwYGAv9sZjc55wqdc7vM7D/wAmaARZHJqjpFrGB3377m26NPaWmCKvXsikgcFbUVkAZZaQdW\nJsnJHERV6DPC9XWEgildWDoRkc6VyARVDUC9/96afI7YCdwN/Lrjita9VdQ1D3azB4+gOrCecFUF\noX4tLhclIp3AObcUWNpk2w1R79/DS1GOde5DwEOdWkCAhgYvsG06Zhe8VOboWZqj1IRrSAs2nqAq\n0rOrdXZFJJ7KmnIv2I1+OD98DFStpHzzBgaOjTkVi4hIt/H2229nbNq0KXXBggVJr/zTahqzc+73\nzrkTnXMnAsuBf4t8jnrNcc5d5ZzrM1MRV+6rAprcPA7JA6B8zaquKJKI9AS1/rj+jIwD2/r7Y+la\nSGWuDTcfsxsKhAgFQkpjFpG4Ig/nI+vsAmSPHA9A2eqVXVImEZFklJSU9FuyZEn/1o9sLqkxu35g\n22zh4r6oot4LdqNvHjmjJwBQtlbBrojEUeP3wjZNY4YWg91YaczgpTIrjVlE4qmsi/FwfpzXm1v+\n0QddUiYRabsf/vCHI/7jP/5jaOTzFVdcMfLmm28eGn3Mpk2bQqeccsr4iRMnTpk4ceKUZcuWZQIs\nXLhwWH5+fmF+fn7hokWLhgJ89NFHqePGjStcsGDB2Pz8/MIzzzxz3DPPPJN9xBFHTBo7dmzR66+/\n3g/gqquuGnHWWWeNO+aYYwrGjh1bdPvttw8BaGho4NJLLx2Vn59fWFBQMOX+++8fCPD8889nT58+\nfeKcOXMOHTduXOGZZ545rqGhAYAVK1b0O+qooyYWFhZOnjlzZv7nn3+eAjB9+vSJP/jBD0ZOnTp1\ncl5eXtGLL76YVVNTY7/85S9HPPfccwMnTZq0//qJSmTM7neAJc65nf77FjnnHkmmAD1VRb3XuGx0\n8xg9AUqg7OPVXVUsEenuYgW70WnM8U6LF+ymZKhnV0Tiqgj7D+dToh7O53qjOco2fNglZRLpLS7+\ny8Wj13y9pl9HXrNoaFHVQ/Me2hRv/7//+7/vOPvss8dff/31X9fX1/PMM88MfO+999ZFH3PZZZeN\nmTVrVvkNN9ywIRwOs3fv3uCKFSv6PfbYY4NXrly5zjlHcXHx5JNPPrl8yJAh9Zs2bUp/8sknPy0u\nLv582rRpkx999NHBJSUlpY899tiAW2655ZATTzxxA8C6desyVq5cua68vDx4+OGHT/nWt7619403\n3shcvXp1xrp169Zu3bo1NH369MmnnnpqReT4999//9O8vLy64uLiScuWLcuaPXt25ZVXXjlmyZIl\nn4wYMSJ8//33D7z66qtHPvXUUxsBwuGwrV69et2TTz7Zf9GiRSPmzJnz8U9/+tMvS0pKMh955JEv\nkv17JjJm92HgGLxxuQ+3cqwD+kiw6zVYG43Z7ec9aCj7bF3Mc0RE2tKzG24IU+/q4/fsKtgVkTgi\nmWhNJ9QEKPtifZeUSUTabuLEifsGDBgQfuuttzK2bt2aUlhYWDV8+PBG8ym9/fbb2U8//fRnAKFQ\niMGDB9e/8cYbWd/85jf35OTkNACcccYZu19//fXs+fPn7xk5cmTt9OnTqwEKCgqqTzrppLJAIMAR\nRxxRdfPNN4+IXPf000/fk5WV5bKyssLHHnts2YoVKzJXrFiRfe655+4KhUKMHj06fPTRR1e8+eab\n/fr3798wderUyvHjx9cBFBYWVm3YsCF10KBB4fXr12ecdNJJBeD1DOfm5tZFvmP+/Pm7AWbMmFF5\nzTXXpLb375VIsDsO2Br1XoBKfz3dWDeP8k0buqRMItIDtCHYjUxA1XSCKoD0ULrSmEUkrspYD+f9\nmZnLtm30Js0LtGUlShFpqQe2M1100UU7HnjggSFff/11ykUXXbTziiuuGLls2bL+AKWlpTFTNpyL\nt3ospKam7t8ZCARIT093AMFgkPr6eovsM7NG55lZi9dNS0vbvzMYDBIOh805ZxMmTKh+//33Yw6N\njXx3KBRq9N1tlcgEVZ875/ZFvW/x1d4C9RQVrhZzB5b+gKgnpXu/hvKmqzOJiNCmYLc27D1cUxqz\niCSrosGrcxrNMRJ5ON9QC18knRUoIl3sggsu2PP666/3/8c//pH5rW99a+/ixYu3lJaWfhgJdI87\n7rjy2267LRcgHA6za9euwEknnVSxdOnSAeXl5YGysrLA0qVLB5544olJBSwvvPDCgKqqKtu2bVvw\nnXfeyZ45c2blCSecUP70008PCofDfPnll6F33303a9asWZXxrjFt2rSaXbt2hV555ZVMgNraWisp\nKYm97qIvJyenvqKiok1P5fQor40q2EdmQ6jRE479wW4a8KHGwYhIDLGC3exsMIs7ZjfSs6sJqkQk\nWZUN3sOyRmN2o9sra9Z0RbFEpB3S09PdjBkzys4888xdoVDzRN277777i+XLl2cXFBRMKSoqmrJq\n1aqMmTNnVp1//vk7jzjiiMnFxcWTL7jggu3HHXdcUg2Iww8/vPLkk0/OP/rooydfffXVW/Py8uou\nuOCCPYWFhdWTJ08unD17dsFNN920ecyYMeGWyv7EE09suO6660ZNnDhxSmFh4ZTly5e3uGbr6aef\nXv7xxx9ndNYEVZ/hjcVNhHPOjU+mAD1VpdWR5RovxN7s5nH00V1QMhHp1mIFu4EA5OS0msasnl0R\nSVYF+8hoCBIMBPdvy07105gj7ZW5c7uodCLSFvX19axatSrrqaeeijl2cvTo0eFXX3212b6FCxd+\ntXDhwkZLxU6cOHHf+vXr10Y+/+lPf9oYb19+fn7N448/3iiTNxAIcO+9924GNkdvnzt3bvncuXP3\n9xxHTy41Y8aM6pKSko+alu/dd9/dv+2QQw4Jb9myZTXAsGHD6tesWdOmSZESGbO7nMSD3T6jwurI\novH4uch4mPLMUPMnpdXVMH8+PPVU4/U1RaRviRXsgpfK3JZgN5TBnpr4sziLSN8WyUSLFgwE6ZfS\nj/IhQbVXRHqYlStXps+bNy//9NNP3z116tTari5Pd9dqsOucu/AglKPHqQjUk2mNJwgLBoJkpmRS\ndkhW85vHSy/BkiXw8sswb95BLKmIdCvtCHbTQs0nqMpIURqziMRXaWGySGm2PScth7JhKfCW2isi\nPUlxcXHN5s2bD/o6p3fccceXB/s7O0IiPbsSQ0Wwnixr3suSk5ZD2dAsWLYGdu+Gzz7zdtxzj/fz\n7rth9Gjv/aGHHlhfU0T6hmo/MG0a7A4YEHfMbm19CxNUaekhEWlBRSBMJs2Hw+Wk5VA2KADr1sH2\n7bDJn1RW7RUR6UWSnqDKzPLN7Pdm9rGZVfo/HzazCZ1RwG6pvp7KFEdWoHkvS05aDmUD+sG2bfDr\nX0NxMRx7LLz6qnfAW2/BjBne9sWLD3LBRaTLdUIas3p2RSSeymA9WRanvZKdCvv2waJFB9ory5Z5\nB6i9IiK9QFLBrpnNBv4BzAXeAf7b//nPwGozO6GjC9gt1dRQkQqZgeZjWbLTsinP8tOFTj8d7rwT\nwmHvBVBR4U1Gc9dd8POfH8RCi0i30NHBriaoEpF4nPMz0ZoHu9mp2ZRn+M3A44+H//ovr63S0OBt\nU3tFRHqBZNOYbwf+DpzmnKuIbDSzbOBlf/+RHVe8bsoPdrNCzYPdnLQcyur9icfWroUxYw7cOMBb\nXmTuXLjiioNUWBHpVtozZjfYvMGaHkpXz66IxBYOU5EKg4Oxh119FtzhtUvUXhGRXirZNOYpwK+j\nA10A51w58GugsKMK1q3V1FCZAlmhzGa7ctJyKHM1XsP17bfh8su9GwbA8OEQDMLSpQd6ekWkb4kE\nu01nOR0wwAt2XfPJ71tLY65rqKO+ob7DiyoiPVykvRKM83C+rhwmTPCGWv3kJ15PLkBurtorItIt\n7NixI/irX/0qt63nJxvsbgZS4+xLBbYkeiEzm2NmH5nZJ2Z2XYz9aWb2pL//b2aW528fbGavm1mF\nmf0myfJ3jOpqr2c3JU6wW1sGRUXw6KPw5ZdeozY1Fb79bXj8ce9mUlraBQUXkS5XU+M9AEtpMjtq\n//5QXw+Vlc1OqQ23MEFViteIVSqzSOfoDe2VzFC/ZruyU7MPtFfefBOqqrz2ysCB3izMaq+ISDew\nc+fO4IMPPji0recnG+z+GrjJzEZGb/Q/3wj8IpGLmFkQ+C1wOl5v8b+a2ZQmh30P2O2cmwD8p//d\nADXA9cDVSZa9w4SrKqhJgczU5sFudmo25fvKodDv5L7iCm9W5mHDvNkOzzkHduw4sF9E+paaGi+F\nOZLxEdG/v/czRipzaz270ce0qrraS02sVnAs0pqe3l45MOyqebCbk5ZDeW05rshvj9xwA+zaBaNG\nee0UtVdEuqVbb701d9KkSVMmTZo0ZeTIkVOPPvroguj94XCYSy65ZFRBQcGUgoKCKbfccstQgL/8\n5S/ZkydPnlJQUDBl/vz5edXV1QYwcuTIqZdffvnIww47bFJRUdHkN998s9/MmTPzR48eXXTrrbfm\nAjz//PPZRx555MRTTjll/Pjx4wvPP//8MfX1XkbZvffeO6igoGBKfn5+4Q9+8IP9MWK/fv0Ov+KK\nK0ZOnDhxyje+8Y1JmzZtCgF8+eWXodNOO218UVHR5KKioskvv/xyJsBVV101Yv78+XnTp0+fOGrU\nqKk333zzUICf/OQnozZt2pQ2adKkKZdeeumoZP9eyY7ZPQHIBjaY2TvAV8Aw4Bj//Wx/EisA55z7\nbpzrTAc+cc59CmBmTwDzgA+jjpkHLPTfPw38xszMOVcJvNmVsz9XVuwGICstu9m+SM+uO/ts7LPP\n4JZbvF7dIUO8mwZ4n0Wkb4oEu01FB7sjRzY+pZUJqoDEx+1qDU2RZPTo9oqrqqIyFbJSYy89VNdQ\nR+2/nUd6uB6uvdbLOFF7RSRhF1/M6DVraP40qR2Kiqh66CE2xdt/7bXXbr/22mu319bW2owZMwp+\n+MMffhW9//bbb8/9/PPP09auXfthSkoKX331VbCqqsouvfTScS+//PJH06ZNqz377LPzbrvtttwb\nbrjha4DRo0fve//990u/973vQEh8kAAAIABJREFUjb744ovz/va3v5VWV1cHioqKCq+99trtAKtX\nr878+9//vqagoGDf8ccfn//II48MPPHEEysWLlw4cuXKletyc3PDs2bNKvjDH/4w4IILLthTXV0d\nOPbYYysWL1685bLLLhu1ePHi3FtvvXXrpZdeOvqqq6766rTTTqtYv3596mmnnZb/6aefrgX45JNP\n0t9+++2P9uzZE5w8eXLRNddcs/3222/fPHfu3IzS0tIPm/81WpdssDsTqAe2AmP9F/5ngFlRxzYf\neHbASGj0H3EzcHS8Y5xzYTPbCwwGdiRZ5g5XWeWthRkv2A03hKk5+QQy5sw5sCP65iEifVe8YDey\nhmWMtXb3T1AVaj5BVaRnt8U0Zq35LdJWPbq9Ul25B2exM9Fy0nIAKBuVS/ovohLzcnPhgw8OVhFF\npI2+973vjT7++OPLzz///EYpYa+99lrOZZddtj3FHy41bNiw+r/+9a8Zo0aNqp02bVotwIUXXrjz\nt7/97VDga4Bzzz13D8DUqVOrKisrAwMHDmwYOHBgQ1paWsOOHTuC/r7KKVOm7POP37VixYqslJQU\nd8wxx5SPGDEiDLBgwYJdy5cvz7rgggv2pKSkuPPOO28vQHFxceUrr7ySA/DWW2/lrF+/fv9EAhUV\nFcHdu3cHAE499dQ9GRkZLiMjIzxo0KC6zZs3JxurNpPUBZxz49r7hT6Lsa1pcJzIMfG/wOwS4BKA\nMWPGJF6yBFREgt2MnGb79t88asv297gA3s1jw4YOLYeI9ECJ9Ow2PaWF2ZgT6tldvBhuvLFxL01k\nDc3aWm+NzeuvT/x3EOk7enR7paWH89n+trLaMoZmRg2HGzLEG3YlIq1qqQe2M911112DN2/enPr7\n3//+i0ceeWTAL37xixEA991330bnHGbWqA5yMSa/jJaenu4AAoEAqamp+w8OBALU1dUZgDUZfmVm\nLV43FAq5gD/pXSgUIhwOW6QsJSUl67KyspqdnJaWtn9bMBjcf057JDtmt6NsBkZHfR4FfBnvGDML\nAf2BXYl+gXPuPufckc65I3Nz2zyBV0yRYDczvXmwm53q3TzK95U33qGeXRGBNgW7tfW1pAXTmt1o\nIMGe3euv99b8Bti3z/upNTRFEtGz2yv+sKtY7ZXIw/ny2hjtlV27vAnzRKTbWbFiRb/FixcPf+qp\npz4LBoN85zvf2VNaWvphaWnph8cff3zVP/3TP5Xdc889uXV1dQB89dVXwcMOO6xmy5YtqWvWrEkD\neOSRRwbPmjWrvMUvamL16tWZpaWlqfX19Tz99NODZs2aVX788cdX/u1vf8veunVrKBwO89RTTw2a\nPXt2RUvXmTlzZtmvf/3r/U/Y3n777ebTxUfp379/fWVlZZtj1jadaGajzWyGmZ3U9JXgJd4D8s1s\nnJmlAucBzzY55lkgMub3HOA119pjiYOkosZrjGb1G9hsX3TPbiNDhkBZ2YGGpoj0TW3s2Y01XhcS\n7Nk1gyuvhClTGm+LrKEZI4gWEaCnt1eq/Z7dFoLdmO0V57zhDyLS7dx5551D9+7dG5w1a9bESZMm\nTVmwYMHY6P0//vGPt48aNWrfpEmTCidOnDjlwQcfHNSvXz93zz33bJw/f/74goKCKYFAgKuvvjqp\nFI7DDjus4ic/+cmogoKCwjFjxtRecMEFe8aOHVt3ww03bDnhhBMKJk+eXDht2rSqb3/7283HY0W5\n7777Nq1atSqzoKBgyvjx4wt/85vftPiUb/jw4fXFxcUV+fn5hZ0+QZWZHQo8ijdhAxxI3XH+ewcE\nW7uOP6blcuAl//iHnHNrzWwRUOKcexZ4EPiDmX2C94T0vKhybARygFQzOws41TnXpkHLbVFZ7T0I\nyerXfIxb3JtH5Gntjh0wYkSnlk9EurE2jtmNG+wm0rMLUFcHa9Z474cP9+qiyBqaoXYPiRHplXp+\ne8Vri2Rl9G+2L6H2ypAhnVo+EUne008/vbGl/SkpKTzwwAOb8bJO9ps3b175vHnzmtU/W7ZsWR15\nf+WVV+4Edsbal5GR0bBkyZJPm55/2WWX7brsssuaZbNUVVX9PfL+oosu2n3RRRftBjjkkEPCsa5z\nxx13NMqaWb9+/drI++eee+6zWL9rIpJt4TwAjAF+BJQCbe6mdM4tBZY22XZD1PsaYH6cc/Pa+r0d\nocJPUc7MTCLYjdwwFOyKdBozmwPcidcofcA596sm+9OAR4BivMp8gXNuo78u5jrgI//Qd5xzl3VK\nIeMFu/36QTAYt2c31uRUcGCG5lZnY45eK/Pcc2HWLLj4Ym97UVHCxRfpa3p0e6Xaq08yYzycb3HY\nFXjjdidN6tTyiYh0tmSD3aOAC51zf+qMwvQUFf74lqzswc32RSZ8iDkGBjRuV6STRK2HeQre08z3\nzOzZJr0o+9fDNLPz8NbDXODv2+CcO6zTC1pTE7u3xMxLZW5rGnNrPbtFRTBxIqxdC1995a2heeaZ\n3lIjItIrVdZ6Q+ey2vpwXkQEmDt3bvncuXOTGuPbXSQ7Zncz7ejN7S0q6yoByMoa1Gxfq2lBHTHD\nYXW1N9auOsF1NUX6hv3rYTrn9gGR9TCjzQN+779/GjjZYs361Jni9exC3GC3tr621TTmyIzNLYos\nP/SVvyRfaqrG64r0YhV+WyQrM4n2SkcGu2qvSO/U0NDQoJtnN+H/t2iItz/ZYPcXwP82s+YLtvUh\nFXVVAGTlNO+dOSg3j5degiVL4OWX238tkd4j1nqYI+Md45wLA5H1MAHGmdnfzWy5mc2is7QU7A4Y\nkPyY3UQmqAL4+muo8uoutm1LuLgi0nNV7PMezmdmNw92+6X0I2ABtVdEkrdm+/bt/RXwdr2Ghgbb\nvn17f2BNvGOSXWf3D2Y2CdhoZu8ATafqc86578Y4tVepCFcRCEJajMZnRiiDoAWb3zwG+Teatt48\ndu8+0Ctzzz3ez7vvhtH+igiHHnpgghuRvqk962FuBcY453aaWTHwjJkVOuca/UPukPUwq6uT7tnt\nkAmqPvXngsjLO9CzKyK92v5MtBjDrsyM7NTs5sOu0tMhK6vtmWhqr0gvFw6Hv79t27YHtm3bVkTX\nLeMqngZgTTgc/n68A5KdjflC4KdAPXAEzVOau8VU+52tor6arIbmiyuDty0nLaf5hA8pKTBwYMI3\nj+q6auY/NZ+n5j/l9dwsXgw33ghpad6SAABvvQUzZkBtLSxa5K2lKdJ3JbMe5ubo9TD9ZUJqAZxz\nK81sA1AAlESf7Jy7D7gP4Mgjj2xbfddaGvOnzSYopCZcs38ymaYS7tmNXPfYY+Hxx71l0FJTEy62\niPQ8FXWVEIw9QRV42Whl+8qa7xgyJKmH843aLNHtlQY/s1DtFelFiouLvwbO7OpySGKSfRpxE/Bn\nINc5N9I5N67J69BOKGO3U1lfTVY4/p8uOy27ec8uJHXzeGnDSyxZv4SXN/ipP9dfD3feCYHAgbV6\nKyq8z3fdBT//ebK/hkfjaaT3aPN6mGaW609wFVliLR9oHnV2hJoayIizfnobenYDFiA1mJp4z+7R\nR3s/v/460RKLSA9VWV9Neh0Eg7H7NnLSctrdXoEmbZbo9kpdnXeA2isi0kWSDXYHA//tnGtxseDe\nrqKhtsVgt603j93Vu1m1dRWrtq7inhIv9efukru9bdv+zp5LvgPf/Gbjk+bOhSuuaPskMxpPI72E\nPwY3sh7mOuCPkfUwzSzyBPZBYLC/HuZVwHX+9uOBD8zsH3gTV13mnGu2ZlyHaG3MbqwJqsLxJ6gC\nL5U5oZ7dkSNhrL/2vFKZRXq9ivpqssLx2wdx2yu5ua0Gu3HbLNv+zqr5M9kz958an6D2ioh0gWSX\nHnoTmAy82gll6TEqXC2ZDcG4+1u8eWzcGPe8xe8u5sY3biQtmEZK0FsO5K1NbzHjwRnU1tey6PiF\nXL80aqk/M1i6FMJhCCXxn1LjaaSXaut6mP5yap2/pFo47L1aSmMuK/NS/wIHHqi11LMLXipzQj27\nhx4Kw4Z5nxXsivR6FQ01ZDa0nIm2t6b5AzaGDIF161q8dqTNkhpIJeDXV9Ftltu2hbg6crDaKyLS\nRZLt2f0h8L/M7N/MbLCZBZq+OqOQ3U0l+8iqj19ZxxyzC6327F5//PXcOedOAhagYp+3Nl7FvgoC\nFuCu0+/i54PPPnDw2LFeg9kMSkuT+wUWL4biYm/s3qv+c4sVK7zxNMXF3n4R6Xi1td7PloJd56C8\ncf3RarAbSiLYHT7c+6wZmUV6vcqGWrLqOz4TDQ60WbADS5/tb7NMu46frPTX8J4y5UBvblvbK8cc\nA6+84m37v/9X7RURSViywek6YCrwCPA1UBfj1etVWB1ZLiXu/uzUVsbsutjz2pgZVx59JWcUnNFo\n+9yCuVwx/Qps6lT47W+9jVdd5Y1befhhKCxM7he45ho44wxv7G847G2rqmr/eBoRaVmNvxZuS8Eu\nNEtlrgnXkBZMi3vZ9FB6y+vs1tTAli3q2RXpYyqoJbOhhYfzqS0EuxUVB+qsGCJtlqlDpx7Yhnlt\nlrN+gT30O2/j1Vd72Sq33ZZ8e+VHP4ITTvDG/tbXe9uqq9VeEZGEJRvsLsKbpGpRC69er8LqyCL+\nLKYtpjHv29es1yZaXX0dL6x/AfNXSDGMpeuXEm4Ie09Gt2zxDrzoIm925z//OfnxLz/7mTfuZcSI\nxtvbO55GRFrWWrAbSceLEey2msbc0pjdzz/3HrIdeij06+ctK6JgV6TXq6SOrJaC3ZbaKwA7d7Z4\n/br6Oj746gMABmcMJhgIem0WVw+bN3sHnXUWTJjQtvbKwoVeT+64cY23q70iIglKKth1zi10zt0U\n6wUsB8Z2TjG7l4pgmEzi9+y2mBYELaYGle4oJWABig8pBmDG6BkELEDpDj/1Z+NGLw0xOxv+5V/g\nL39JbmZC5+Cpp+DMM70GdSjkBc3gBcCRnl4R6XhRwW51XTVzH5vbOEiN9OzuOTAHoHOO2voEJqhq\nKY05MhNzpME4bJiCXZE+oNVMtLRsKvZV0OAaGu+ItFdaWS6xdEcpzl918qiRR/H4tx4/0GbZuNGr\n0wYOhPnz4bXXklu71zl45hk4/XRv9vhQ6EAQrvaKiCSoXWNszWyCP9PpZ3iTVp3bMcXq3ioDDWRZ\n/IZnTlpOyzePFoLdoqFF7Lh2x/6F4Osa6thx7Q4Kc/3Un40bIS/Pe3/uuV6a0UsvJV74f/zDe9p6\n5JFeGtATTxyY9AGSH08jIomLCnabLS8GMdOYww1hGlxD+3p2I8Huof7qcAp2RfqECguT2UommsNR\nua+y8Y4E2ivgtVkiacyf7v6Uc6acc6DN8vnnB2Z/P/dcLw35z39OvPAffuhNThXdXnn8cW+fc2qv\niEhCkg52zay/mV1iZm8CHwE/A3YD/w6MaPHkXqIiVE9WIP74uezUbO84f5Kp/SJPJFt4smlmBC3I\nht0bANiwawOpwVQskqoTHeyeeCIMHgx//GPihX/uOS/t5/9n777joyqzBo7/zsykJ4TQQu/Si4qA\noLJYsYDiAuqudXdd113761pX1+jadnVZ0bWsiuvasGJBsaCIDRAEFUFAiqF3Aull5p73j2eSTJIJ\nBAmmcL5+xmTu3HvnmRvm3PPc+5Tf/96dxMaNg+OPd8v+/Od9709jjKmx7F1ubttV+RuqTi+2aSHZ\n8eHveURlt7Qv7n7f2Y2PLx+cqnXrWh+gKuqdamNMncrzB/fa7Qqo2hqthpVdoCxf+THrR0JeqDxn\nicxXBg6EQw5xLctq6u233c/IfOWoo1ws+93vLF8xxtRIjSq74ZGWTxWRF4FNwGNAZyA8WhJXq+p/\nVDVK293GpSRUQrEfkvwJ1a6zvyePDTkbKA4V0y2tGzsKdpRPC+B5sHZt+ckjJgbOPNOdEDyv2v1V\nMG0aDBnikt3Y8AmweXM4/HDXxMj6vxhzwLz29fMAXPnx9Xy65lMAPl/7OcMnD2fQ44N4ctWrbsUo\nld24QPUX2Gp0Z7dr1/Lv9wG4sxv1TrUxpk7l+j2SanBxvsoMEqUX5/eSr2zP3052UTZ9WvahxCth\nQ054XBHVind2RVxl9eOP3YCYNTFtmstN2rcvz1fi42HECDeThOUrxpga2GtlV0TuBzYA04AxwOvA\nyUBH4K/AQRVtSpsXJx/Ayu7KnSsBGNVtFOCaBgGwaZMbkbBTRNfoIUPcgFdr1uy98Js2wfz5MGZM\n1ddOOgnmzt3j4FnGmP1zUa9zACiKkbI7sXkleWXTi11zcoZbMaLPbq3d2S1twgyusrtzp4sn+yGr\nIKvsrnS0O9W7CnftZQ/GmANFVckNeCT79tztCqLkK2lprjK5lz62pXd1T+p6knu+0z1n1y43Z3jp\nxXlwUwWFQjVrfrx9O8yZ4waiquzEE90cwKUDYBljzB7U5M7u/wGtgOlAR1U9V1U/UFUPiD6HTiNW\n2jQ5OZBY7TrVnjyaNHF3Y2ta2e3uKrulJxMyM93PyJNHaTOeJUv2Xvjp093PiMpuadPDomNHuMEe\nZs3a+36MMT+JhOfZPaLr0RWWn3bIaW56sYQEdwcj4s5uUchts9fKbnV3dlWjV3bBDfqyHy6ZdgmD\nHh/EEY8fUXZHN/JO9UNf/Gu/9m+M+ekKg4Wo/MSL834/NGtWd/nKe++5FmtR8pXCkce4BaXz7hpj\nzB7UpLL7FJADnAYsF5F/i8iQA1us+iu3yN35TI5NqnadlLhws6CiSndJRdzd3YgrpdH6ua3cuZI4\nfxwjOo0AIq6Uhk8ehe1al2/Tp497rSYnj2nToEMH6F8+J15Z08P0XDclyQfWBNGYAyY8QNXHm+YA\nEPC5KUGm/TDNTS8Gbvqhfe2zG5NQ/Ty727e7geyiVXYjmjL/lD63c9bPITk2GREpG5E1ryQPn6c8\nOB1uyTmsxvsyxtSu0ovzST/l4jy4fCWisltdviIIIzqNIOALlLdEC7c2K2yXXr5N9+7ugv/33++9\n8NOmue5Whx9etqg0X3k/cSO0agUzZux9P8aYg95eK7uqejHQGjgPWABcCswRkaXADRxkd3c3Z60D\noElMSrXr7MvJI1o/t1VZq+ia1pWm8U1pkdii/OQRrux+EFpevk3TptCu3d4ru4WF7sQwZgxZhbuq\nND18eNGT7D7yMArfnWZND405UMKV3fwY1/vjjpF30DKxJUEvWD69WGpq7Q5QVXkkZigfqCqisruv\nfW7XZ69nQ84G7jruLn7Z+5cVXjtlW1OumAfy2GOwcKF77LK4YszPqazb1R4qu9VenAfXb7cG+UqH\n1A4kxiTSuWnnKnd2P/JWlW8TEwM9euw9XykpcXd2R48mq2h31a4SC//DzqMOp+SD99iVv3Nvh8EY\nc5Cr0QBVqlqoqi+o6iigA3AzEAJuxPXZvVdEzhPZw3w8jcSbS98gNghHJfasdp09VnZbtiS4dfMe\n+7kt376c7s26A9AtrRurslaRVZDF9qULKGnRjEcW/7fCNtndOxBcvGjPBZ850w0KMWYMD817iEGP\nD2L45OF8tvYzAD5b+xl3xs0lftUa/vfW3/b1sBhjaiJc2f3XhCcAOLzN4dx8zM2ENFQ+9UdqatQ+\nu3H+6geZiQ/EE/SC5XeHI0Wr7Ibv7OatXfWT+9zOXT8XgMFtB/PuincJ4KNrOO98P2UrIQE+/xyG\nD3d99R56qNp9GWNq3/z1XwLQJbZVtevs7eL8vuQrXdO6sjprNVkFWWz5fj6hpEQeWvl8hW2yurYl\ntPi7PRf8s89cf9/Ro6vNV66XD4nZvpOXp9y6T8fEGHPwCezrBqq6Cfg78HcRGQxcCJwNPAM8BKTV\nagnrEU89Xl3xJqNWQeox1X/MaCePgpICJrwygTeapbHry28Z9Pgg4vxxhDQEwBfrvmD45OEUhYqI\n8cVwUjc32EO3Zt2YvW42D817iCPnvE7TeGHmjzMrbHN3URFXfB/j+rf4qrl+MW0aJCXByJHcGjeK\npvFNufHDG8kvcaMi5pfk81H3WCDElVs67+eRMsZEVeDuvi7Nd038+qf3Z3iH4WTMymDi3Im8NP6l\nKnd2s/Ndn10J7bkZM7g4U3qnpsyKFe5nZN+5cGV37oI3OWHzFcT548qmN4uMRXeMvINbfxE9mZyz\nbg5x/jji/HH4xMeLE15i3Icb6f/D1axKVQoDkJSX50ZPffBBuPzymh0jY0ytePG7KbTOgaNb9Kh2\nndLRmKPnKy0p2LRuj/lKYkwi5/U/D3AX5+dvmM9D8x6i/2cv0CNJmJn5cYVtrs8p4vZMcRffE6u5\n4/z22xAXByecwK2Jp0fNV2Z2jwOC/H5dy/09TMaYRm6f59mNpKrzVfVy3Py644FPaqVU9dS8DfNY\nn7eRCUtwCVw1og3lX9r8Z11MPs3zlEknT0LRsjsxucW5+MTH3479GyVeCd3SugHu5LF291puOOoG\nBpe0ZGUzocQrqbDNwON/RUxRiZt8vRree+8yp1cyBX5FRLhy6JUc1+W4CusU9ugKgwcjDzzgBqsy\nxtSu8J3d73b9QPOE5rRJbkNKXAqXDLqEV79/1fXPr9Rnd/Y8t803C/bcjBmI3pR57lzXtz8pYpyB\npCRISuK4xL5MOnkSgpTdQS6NKw+e8iC3jLil2vecu2Eug9oO4rA2h7H9+u2M6zMerrySx3J+QUEs\nPDw4vGKTJm6eTJsmxJifTXZRNu+seo+zloA/ofpmzHEBd8EqsrJbmq+s9ueQnF3IpFEPRM1X/n7C\n38kvyadbM5evdE3rSlZhFpcPvpyjvXasbkaVfOXIUb9FVN1oytXw3n2XBT2bUBDrK8tXju96fMWV\n2raFk09GHn645lMZGWMOSvtV2S2lqiWqOlVVx9bG/uqrV5a8QowvwJgfgITqRzeM8ccQH4hna97W\nsqY+j85/FIAvCn+ArCyGtxlCYkzFE9DoHqP5RadfAFRoFuSpx7pda0jbspsf+repss3xo690T6rr\nB5OZiS9zDS+02lLW16YkVFL2e8/mPRGEpTuW8fZlJ7pmjy+/vE/HxhhTA+HK7qId39M/vX/Z3dSr\nhl5FUkwSv576a4pSk/Gydpd1dX37PbfN66/EV9v9NfLObgWe56bvGD68alnS05GtW7ly6JUMaV9x\nzMGy0aGrqaAWh4pZsHEBw9oPQ0SI9YfnwCwp4ajX5jNqJfzjGCEnXtyIz+PGQXHxvhwpY8x+eHPZ\nmxSFijhnMXvMV8D1292ev71KvjIrbzFSUsIxaYeSHJNcYZvRPUZzQtcTACp0uwL4cdePtNyWz/K+\nVfOVU8/4s3tS3SBVW7bgW7aMl1ptq5CvvL/yfQB6NO+BIPy460f+e9Ghrk/x5Mk1OyjGmINSrVR2\nG7uCAjhttPLK969yUvOhNC1kj3d2wTVlnrNuDoMeH8SRTx7JjNVu1MCvg+sQVY57dBi7CnfhEx8+\n8SEI01dMZ/mO5UDVk8eq1QuguJi3mmwCQML/TV8xnWCvcBOlSpXd0jkwM9/8HwCzOpf3m5myeAol\nXglD2g5h2eXLePaXz+ITH+dtepi1RxwC99zjEmVjTO0pLMTz+1i8bQkDWg0oW9yuSTueHvs08zbM\n48r0hUzZejyDBsHgwfDd9CPh49v4el58td1fq72zu2yZqxlHq+y2bg1btlASKmH2utluUbIbuKrC\n6NBRfLP5G4pCRRzZ/siq7yfC7R/DjgTlyX9d4JojTp9ufXaN+RkUFLipaZ9f9CKdktpx5HpqlK98\ntfGrsnzlg9Wukjm/2LUWO/mJkews3IlPfAR8gfJ8ZXvFfKVrmhsXYNWG7yAri9fTNgPgF395vtK1\nsxuoqpp8ZfWbTwMV85WXlrxE0AtyWOvDWH75cqaMm4Jf/Pxp5QN8f9JhcP/9+z1nuDGm8bLKbg28\n/z5M/2Y+67LXMmFdipt/brBro1d6YimolGM2iWvCIc0PYdLJk/DUK5uW4/32xRQEIJCU7Pq5jXuR\n03ueTrOEZgjCvA3zCPgCdGraCaCsedCqHxcAsDJNGZA+gNE9RtM8sTmCsKx4o5tSqNLJo3Rgh0//\ndwdftYXFLcv7zVz4xoUA3H/S/QCc2/9cFv1xEUWhIu78VTtYvBjeead8Z7m5sHy5mxDeGPPTFBby\nY+s48kryGJA+oMJLv+z9S2446gYe99ZxQWgyMTGKKnhFifBJBgXbWiPiur/eUql1ceU7u6VxqXiW\nq8Ry1FFVy5KeDps3s3jrYkJeiOEdhrPumnV0adqF4lAxX238qtqPUTo4VZXKbr9+8MILDN0AI5oM\n4F8FMynJ2uFq6K++ug8HyhjzU7z/Prwzcwcfrv6Ac6Q/AnDIIcCe85VOTTuV5SulPmhfTGEANDUF\nn/iY8sspnD/gfBJjEhGkLA6UVnJLf67O/BqA5c2VXi16ce6Ac8u2WbZ7FfTsWW2+8sHkm/k6HRa0\nKc9Xzn/9fBTl7yf8HYCz+53NqitXER+I57bTEmHtWnjhhfKdZWfDggVlLWmMMQc3q+xWIyurfMaM\nRx8Fur6PeDGcOnkOWSPPZFdSOyB8Ynmn6vS0TeKakFOcw3kDziur6AIsSYchv4esUC7Tfz2dCX0n\nMKbHGHYU7GDmuR+Qnb2Nzk07l82/2Sa5DfGBeFZtWcraVMiJVS4ceCFje41le/52PrrwI/q27Osm\na6908rh1xK1MOnkSR2V6nHIu4HP9ZgShVVIrBrUZxNEdjy5bv2/Lvlww4AKeyZ/D1l4d4K67QNWd\nRLp3h169XH/CY4+FW2+tMG2JMaYGCgv5rq37bvdP71/l5TuPu5O+q36HR4Annl3AuHFAvykw/B9Q\nnEL79m6cp8qtiyvf2S2NS5umzobmzcuS3QrS02HLFnbk70BRrh12LQFfwA2SBbzw3QtVtwmbu34u\n7Zu0p3lM+4rJswh89RX4fFx33F9Yl72Ol1e8Ab/8pes7vGHDvh0vY8xeVclXur1PiCBjX1pJfo+B\n7OrlLkrtKV/JLsrmN4f6MrkvAAAgAElEQVT+pkLXhbVNYeClsM3LYerZUzmr31mM7jGavJI8Xh/3\nCtlZm2md3JrkWNfEOSUuhZaJLVm1ZRlbk1zrjvP6n8cZPc8grySP185+ba/5yjGZHqPPBc9fnq+0\nTWlLv1b9yppNA3Rq2olLB13K1F1z+PHIXnDvve5i/PPPu3h3xBFuvIDBg+Gqq/Y4pokxpnGzym41\nHnrI3YwYPhw+nqUw+3raLDqeltt2c+ZHl3HTTREnFtzPyP50KbEpZBdlM3nhZDz18Iuf/q36k54n\nLE6H05IPZ1T3UQCc1mUUgvDeVaey8rM36R5MLSuHiLjh/Hdl8p5rKcQp3U9hTI8x+MTH9BXT3cmp\nb1/XhDDizquIcGX66axOg+0RY9MENcjWvK3837D/q9In75ph11AUKuKR3w2AL790B+Hcc6FjR/jP\nf+DCCyEvzzVz7tYNMjIgJ8r8fMaYqgoLWZTuuiH0bdm3yssBX4DumZfgS9zMlKzrePdd8MUVwok3\nIIEiVq6Ea6+tutvSO7uLlhaycCE85mYIwTd3Nrv6Dmfh11J1mtv0dNixg1eXvExSTBIj253C6NHQ\nr9lg/jDoDzwy/xE25myM+jHmrJ/Dke2PjJ48z5kD/fpx6oDx9G7Rm/tm34eeeaZ77Y03an6sFi2y\ngfKMqYHIfGXWLGDJ2ST8cDxD56/kih+u4KabZa/5Sk5xDs98+wxBL4hf/AxIH0DzAuGHFnBsXC9O\n73E6ACd2PJZYArx/y9ms/vBlugebVChLt2bdWL07kxnhmc5GdR/FSd1OIs4fV56v9OnjKp95eWXb\niQhXdjmHXXGwMWKXJV4JG3M2cvXQq6vkK1cMvQK/+HngnM4u/xkwAM47z408/8wz8H//BykpLnfp\n1cs937Gjdg++Mabes8puNW69FSZNcjcqSoJBCMXR/vOzWCJ9STrlFzz2GAwbBh9+6NavPJ1kk7gm\n7Crcxb/n/Ru/+Hlp/Ess+uMinjzlUT5+Gu7LGebmkps4kfTBIxmyXpnWuZiVLYTuHy2EKVPKytIt\nrRurijfzXp9YOqZ2pFeLXrRMasnwDsN5Y1k4eezb1zXZKZ1TMyz48Uc8MxD8HvRr1Q+/+PHUo3eL\n3kzoM6HK5+7VohdjeozhYe9LCjq2dft75BGXwF5yCfz73zBvnhtc4pRT4Pbb3V3fWbMO0F/CmEYk\nN5dFLT26N+tOUmxSlZeLi2Hmki4MSJ3GjC2fQuo6zj63EASee06IiYF//Qs+qTTufemd3T9eXlCW\n8CaTQ4e85dz/xfDo09ympxP0wWtLX2NMzzF8OjOhrOJ67fBrCWmI/3793yplXLZ+M5m7MmnPkWWV\n6rLk+SsPnfslDBuGT3z8efif+XbLt3wYux5694apU6ttSlnBQw/BwIFV22sbY6qIzFeKS0KgflrP\nvJSdNGPnqF/XKF/ZXbibSV9OKute9e2l3/LkuP8x9wl4dNtQZNYsuO8+Ug4dwsiVQd7uVMzK9Fi6\nz/nB5QhhXdO6unylp58WiS04vM3hJMcmc2K3E3lz+ZuoqstXwFVQIwRnzeSZgeDzXEszv/gB6N2i\nN+cOOLfK526b0pZz+p3D5LzPyOrXHTZudMFo9mw4/3x3t3fmTFi1yj2fNMldpH/zzQPydzDG1E9W\n2a2GCFx5JfTt64EXAy2XsGT7BGb0/z/efkeYNMmN31Q6hlNenpvitrQ/XZO4Jny35TvWZq/lqTOe\n4tQu4xg9Go4/7CJGZkLv2x+GESPcbZrkZEYf8Wvmp+WzO8ajW9Ou6Lnn8ki/RygoCFd2fbv5sGOQ\nk7udXHZ1c2zPsXy75Vt+zPqx/ORRqWnQhhlTmdobjut2At/98TteHP8iSTFJvDT+JWL8MVE/+7XD\nrmV7wXaeeeoqV9n94x9dP+VIPXrAK6+4ponNm7vsdc6c2vwTGNO4vPACvPIK37WWqE2YwVVicwpi\n+FP2W3h4/PnZp+neqxBB+NVZMWzb5mbcuPlm18OgdITj+IAbgOai3xcQCkFREeSRwCZaM9d/VNR+\nvrRuzSedYHvhTgbFT6hQcc3O7M4RzY/liQWTK/ThA7hj8pcAPHzjMD77zC374guXPJ8/eCmSk+0y\na9xYAG2S23Df7PtcU+ZPPuHjV7ZHbUpZ5vnnXfBNSXHJ6fr1+3SYjTnYlOYr/Qd4oH5o9R0bNo/m\n7W5XM/XdBCZNcvFiT/nK6qzVrNi5gn+f8m9O6zqe0aNhVN/zGLI9jp4T/wfHHQfXXw8pKYz+xcUs\nSylkY3wx3dJ7wWWXUZJxF6NPUzomd2OdZPNedxjVbRQ+cWnmGT3PIHNXJou2LKo2X9ny3lRe7gtH\ndzyaxX9azIvjXyQxJpGXJ7xcFuMqu3bYteSV5PHExHPd3eJLL62ar7RrB08+6VqLHHIInHXWHgKQ\nMaaxscruHhQXw8JlOyH9W85ufw95JHPr0nMJheCcc6quf/jhcMUV7sTTJK4JitIysSVn9z27vLnf\nJ3EwcSLccYdbsHEjfP01Y864vmw/3W/4O5uPGM2fllxGwWHD6Za5m3x/iJwYj5O7n1y23hm9zgDg\nreVvuWZBUOXkMXPbl+THQsaxtwMwvs94tl+/nX6t+lX7uUd0GsGgNoOYuHQyXlrTPR+koUP54bXH\nCbVt7e70fu0GpmDDBrj7bndl1aYcMQe7Z5+F888nf+RRrIjLY0CrAVHvcL71FiTEeZyb9xHHJffn\nf989RUFJAXGBOESE1FT461/djYvpN37q+qTddRcJgXjwfPw4Z6Br+dvzDVSEo3teR/y4lLK4BC7p\n3bkTluR1ZmKrE5FZt3D9Gacz6/0iEshn1ixXV/3qP79nTfaPfLT6owofpeNRc/ETg2w5vGx6y9xc\nl0jfM94NpMeRro9gXCCOK4deyYzVMzi/xSpuGhli4vSLYOiD3Pn8x3w0Z3vFqZTefRcuughGjoT5\n891OMzIOyJ/EmMakuBjmL9sIzZdxXI9/UEw81665glAIfvMbV7mNNGBA1XylSVwTLhh4QXm+MkPc\nPLZ33w3vveemEVu4kNHjbi7bT/c//gXOPZeY22/hzumHETdjI57A9vhQhXxlTI8xCMKby990rcFi\nY6vkK7M3zGFXAtwy8q9Aeb4SrctHqYGtB3J8l+N58LsnKU6pfj5hAPr2ZemLD1HSuyeMHetucYPL\nw+66C267zebsNaYRssruHtz+0Ao0rwVdR3zElCUvc3TzpeQF41i0yOVfwaC7gNgvXG/84gs3w8aW\nLZAccJ1OTm15KR++H8fEiW6dRx+Fhb+4hoWn3cqu4adCGzcP3YD0AbRL7gBA0c6+XNz0Na7gQQrX\nbqXrRNeUMKA+jutyXFn5ujfrTt+WfZm6bCokJ0OnThVPHpmZPNtuB919LRnWfljZ4lBxLGPGSLXN\nCEWEa4ddyw87fmDq0qnVHp8VO1Yw+oXR9Hz5GH79l94EmzaBk06C0093fXz/8he46SZ3B3vt2n05\n9MY0Hk8/7fq6H3ss3z9xN4rSP71/lf6uqq6ye9IxBSRSwMUJR5G5K5N3V75b4a7Gb38L3dvm85d/\npOIlpcAttxC6bRK88jKfvH4I0nManDWezm3fYPXqP/BO25O56PXfMn3FdN77sJAWLVxjjH7nH8b0\nLz9AZ/2NDqENnMVLdGE1RUVuFo8JfceTFt+MJxY+UeHjzF0/h4HNh5IQiCOBfI7hU8Btc/br5zAu\n5i1e+roHublu/UuPuJRmdOO57W/wz6E+ZhalQWomX8XczwlTjmTQo4O5+8FN8Nprbj7eAQNcM8Oe\nPeGyy+C//y2bk3PFjhVc+/61XD79coqCRVUOdY2aSBvTCJ1374uQ3Z6+xy/gw2XvckLqfHaGmvLN\nN/DPf7rWHpH5ypdfui70W7ZAkt/lKye1+B2zZiTxz3+6dR59FBYe9jsWjrqJXUNHQcuWAHRJ61JW\nAQ3u7MXCq59hYt/J+Alx/Mvlc94ObXFS2e/pyekc2f5IXl/2Our3Vx2Reds2nm2+nrY0qZDn7C1f\nAXd3d0POBp799tlq11mdtZqxL46lz3PDGHtVK4o6tYPTTivPV265xd2EGDYMVqyo0TE3xjQQqlon\nD+BkYDmwErgxyutxwEvh178EOke8dlN4+XJg1N7ea9CgQbqvcopyNLHPLPWlbNENZ4xRBf3gyTUK\nqjfeqBoIqMbEqL76qlv/8cdVRVRdyqrq84eUuF1lz0sfycmqcXHu9zvuqPieQzIuV26J1djEQk1K\ncuukJAb1hFaPKBloj5sOq1LOuz69S8lA75h1h+qpp6oOGFD2WuaT97vXXrqswjavv+72/cYb1X/+\n4mCxdpvUTclAj336WH1+0fO6MXujLtq8SD9Y+YFe98F1GnNHjKbcnaLnvHqOkoH+6r+jNdi2tWp6\nujtIK1eqvvyyakqKarNmqm++qRoK7fPfwjQ+wFd6MMSVnBzVtm1VTzpJNT9fH/xsspKBvvHpCh01\nyn0PR41SXbBAdcoU93zyA9mqoAUP3K9p96YpGWjr+1uX73P+fH0h7iIF1ReeyNEFv75fu8oPigS1\n2/jHlQx07IPX6tLYASqE1HfI+5rwt0Tlqs5K4jaNS1+tjLpGGXeODjpphH7ZtJluSeys1zBRd5Kq\n93GtNm8WUlDtOvQ7DdzYSrfmblVV1R+2/6AJdyZqz2PnKXj6Lu5D/Eb+q/HxqpelPaet43YoqCYk\nqF50kercue5rf9llqm3ZUCUmkrpG2194nK5tguoRR6hu2VL+Wbdt022tkvWlC4/QUc+OUjLQwB0B\nJQMd9ewozSvOK1u1OFisf/nf20rb+frK1KIa/Ts0jctBE1cqefyrx5Ueb2psym7Nuez/VEFn3r9A\nQfWuu1STklzOUpqvTJ5cMV8RX0iJ3V3lu5mUVH2+cvOHN6svw6/EZ2lsrGp8vCp4enyLF5UMNPmS\nnlW2eejLh5QM9LoPrlPv7LNUO3cue23Li5M1cCt6/dPnVtimJvlKyAvpwEcHKhnosCeH6eSFk3Xd\n7nX67eZv9f2V7+uNM27UuL/FadJdSXrB6xcoGejpT52oRd06q7ZsqXr99aorVqi++67LVVJSVF98\nUTUY3Oe/hWl8DlRcscfP96ibNwU/sAroCsQC3wJ9Kq3zJ+Cx8O/nAC+Ff+8TXj8O6BLej39P77ev\nJ4/VO1frsHt+q6D6m76PuMP04IPqeaoDB2rZSWDNmorbrV/vTib//rfqdTcU63kX79RTT3WV4sgT\nSEKC6oMPqnpexe135mfp1ffNrbJ+ILZEE//SQR+c+1CVsgZDQT1/6vlKBppx83DV2FjVkhJVVb3z\nqsOUDHT19pW6c6dLqBcscHl3ZJK9YIFqVlbV47A5Z7Pe9eld2nVSVyWDKo+L3rhIN+VsUlXVez67\nR8lAz3/5VxosLKi4o+XLXSUcVJs3Vx03zh2AZ59Vff55l+W/+qrqtGmqM2ao/vDDPv29TMNzIE4e\n9TWuZH7ziX64dLo+Nv8x7ZhxtHJzosbEhjQ2tjwelCaUIqqb1xVraXZ5+TuXKxlo5wc6u2Ts6adV\nW7TQUKcuOqB3sbZqpRob62m7JruU3xytZKDd7u+k+bM/UQU9a9haTUlRXb6yQDv3yNa45FwddM/Z\nmvFxhmZmZarecYeWPPIfbZpYpIGA6nUdX1QFvTfwF504UTUQ4ympP+plv71Kp77xnDa57lBNPPU2\nBdUM/qrrhk1QPfFEDfljdELCNFXQYMbfdNYs1d//Xssu2nXs6H6mxhXoy4zXP/GQjmSm/q7dO9o2\nNlPxFWmzU67TVVuW6+aczfrqklf1qnev0gGPDiiLN23vbqG3z7pdN2Zv1CcXPKmSIXrMU8fo6o07\n9Y43ntF2/+iq3ObWlb/Gat8HBusFz16n7yz+VEtCJfv5L9Y0BAdTXFF1lbwbZtygXH6IgurN/V9x\nX7TLL1cv5Omhh7qnPp/qN99U3HbjRtVXXlF9+GHVm/5Souf9fruedlrN85Xcolz9PHO2nn9+xfUh\npFzRQ8f8/d4q23iep396+09KBvrnjKPUA9XcXFVVnfTnY5QM9Lv1C39SvrIjf4f+c/Y/tde/e0XN\nV86bep5uyN6gqqoPz3tYyUB/+cJYLS7Iq7ijNWtUhwxxb9q0qerYsar/+lf0fOWDD1SXLq16cEyj\nYpXdhv8Q93f8eYnIMCBDVUeFn98EoKr3RKzzfnidOSISADYDLYEbI9eNXK+69zviiCP0q6++2mu5\nCt56jYzMD5g4U/C+/CP+bT3Z6HWkxeS/u04vwHPPuUH9brut5l3JJkyAV18tf37YYW7k0lI5OW7c\nhEWL4Kmn3DSVlbVuo4w9AwYPFgYNcgMKJiW5/jYhL8Tv3rqY/81/mT980YTusYeyvlk7XijZSGp2\nH8Yeej/vvANLl1bcZ2kfHs9z3eRuv92N4xAKudH5t293femydnnMW7WUTQXr6NfXx2F9k+jWoiMd\nUjuQm+uaQYnAYwsf5L4v72Rgm/6c1W88Y3udQZeWbYmPBykscANazZyJzvyIok3rWZMKK5vB6jQI\neJCeB61zIakYCrp1pOAXw5HBQ+jZbQitO/VD4uLgo49c26vp0yEx0Q0nOWiQ6wOUnOweKSnQooV7\n+P2webNrLrV0KSQkuObenTq5OYNLRxnLy4N161xz661b8bp0pqh3D4o6tycpITX6YF7FxW7y+t27\nXT+ftDRo3pziWD8xvpgq0yRUoVp1wtSDhIgsUNUjanmf9TKuNP9Hc3bm7wQvQCwpdPj+n6ye+hsi\nQ6/fD61auRkzZs/Gfbl9Pr7tmcqhYzbQa6efpQ+GpxVr3x4++ojpK3tw2mmu2e5//6u0fNh9oT+e\nEsfIjiNgxgwWzdjCwBNb0aKFm4vzvffghBMqlu+77+Coo1xr4XHj4Mfjfkunj59m062PsuHjHxjx\nzRUU5XausM2p/vd5c+CtBD6b5dpHHnkkuno1EgzCjBllb5Kd7cblmjoVjjkG/n6Px4qCdrRhc9m+\ndvYeztjUF/lsbgd8vabhtVwUPiY+enQLcOwRTZjw2N84atEGSo45mawzLmLHwON4adnX3Pvxc7Cr\nE96WPsiGwWhWF+Jit5OQ/g2hLh+R0/0LiN9FahMfx3Y/iiPbD2VIuyG0pBNvf7iWj2fn88PyeOIS\ngzRtWULz1kqntvn0ar6VAUkbaOcV0zQ2ldT4VCQhgbVxRaz2ZbMqlM3GgkI25RayLTuftOQkerdv\nQ792neic1olWSa1oltgcn/hQdeElLw8KikrYXZhDdmEucYEY0hJTaJKYSEzAh8/nwkFkSPA8JSsv\nh225WWTlZ+MPeCQnBkiO99Ekxk8ycSRLHLGeuHhUUuL615TWO4DipHg2xhaxvmgbQS9IalwqTeKa\nkBqfSmpcNbGtgTqY4krerA84a94DTJ/Vlabf3EjBllas8TqQfs81cMMNIMKzz8IFF7iuD5Mn73WX\nQNV8pX9/l5uUvW+eixnffutm95k9251KI6c2i41TLrrQ5StHHOFOz6X5iqpyxfQreXjOk1w0N5UB\nOoB1LTvwctEmfHnd+dVhD/L222U9F8pUzlcyMlwo9Dw3BkFpvrJrlzL/x+Wsy15D377i8pWWHeiY\n2pH8fJevqMKzi58k4/Ob6Jvem3P6ncWZvcfStWV7l6+UFLtuFTNnwsyZlGSuZk1TWJXmchbB5Sqt\ncyG5GAo6t6fwF8Nh6FAO6TaENp37IwkJblj811+Ht992fZRL85UePaLnK4GA6xe9eLHLV2Jjy/OV\nZs3K85X8fJevrFkDW7einTpR1PsQijp3IDGxmu90MOhylexs90dMTYUWLSiJDRDwBSxf2YMDEVfM\nz6uuKrvjgZNV9eLw8/OBoap6ecQ6i8PrrA8/XwUMBTKAuar6XHj5ZOBdVX2VatTk5LFtdw6dB80k\n/8dTwIulqyzndt89nDflNBf9w0IhFwNPPx3iow8OWEFJiasDFRW5mTcWL3Yxo3fv8gQoctq3jh1d\nMA4G3YCF33/v4t/Ike6kkp0deRxdrAwEICdHCQajB6K4OOjSxb3vypUVpuKtwu/f8+vg3q9dO1fu\n0n55e+QvRuKzITYH/EWovwh8JeALhh8hQHGnkEjhZZ4ff8hPXHEAT2MIaQwhYnH/cj1AEfFAPEQ8\nBA+flOCXID4JoSiKoOLeQRR84X/36lM8UVSUkAgegiduXfe/8EfAI8bz8CsoAiqUfXNEUSDkE4Jl\n20JA3ZRPfk8QFUR9iEq4nCFUPDS8rYqABhDPDxoAfKj6QN0ZXnxBfBJEJARS+nmVslLUk5PQinm9\nadGmxV7XO0BJab2LKwDNWxewc0tChWVpaa7yWcrnCw/wdA/ceCPuqteXX0J+PkPavoPP72du57vc\nkMe9e5eNNrp2LXTo4P78Hf/VkTHtjuXhyZtdR+BOnSAzk7FjXRfYBx6Aq66qWj5VF6diY8MLcnPR\nwwchK36AtDQe/cNo/vRNGr01jas+WUfbwq2c2GYJ8V997oaGBtfHbejQ0mzTDZxVSWml+vVbFnB8\n51V8uOYQLryjG+/PaUKfPnDNrZt4ZGIaXom7UOSFBA1/B/1+xU+I4lAg6jFuEbOGI0u+pSc/8D19\n+JyjyaFqGarwFyItl6DBeMhLh4JK/3bjdkPZN10gGAehWKod7kJCEChwMU08xPOhJcmg/ujr7y8J\nhR+eixXqd3FLvHAZQmVlqfJAXTBEw58mMhco/13k588RKlvxpUeX3p32ut7BEldyCgroOPAtdq0e\nC6E4DmMhf/Hdy7j/jna127CSEjeg+YUXlnW33aM95SsFBe58v2NH2XUU2rRxF8mvvtpda+nTp7wb\nbnKyq1uVHyO3LDYWsrOVkpLo56yYGJevgJsxqDbylfbtXYU4Mn+qfqfFSHwOEpeN+gsr5isSCv+M\n9p2omK/El/jxvFiCpfmK4s7baFmuAu6nT4L4cfkKKCrlGZFoebRRcfmKewghIXq+okqMpwQ0nPtE\n5FYa/t4HRQj5BK9CviL4PcGngnj+8FblMUZd6oOHIOoH9SMaAPWh6i+LJD4JIr4QPglSnp9ppRSv\n4jGsiwxmztvt6Dmw+17Xs8puwxc9czjwov27rhw9qlunJtsiIpcAlwB07NhxrwVqmZpCh6ZdGTBm\nCTccm8vhzdcifa9yt2Ej+P1u1PqaWrbMJbIvvujumrzwgrsq2b69yxOTktzPgQPdIysLjj7azb4x\nbpy7wvrb38J997kTycqVsGCBG+w4O9vdFS4pgdRUISXFI0fW07Spj46tmtAuxU/nXkm0bVt+VXTC\nBFdZL71IN24c/OMfboah1avdhcL4eMoGsUlLc3lraqq7mPj99+5ktm6dW6dNG0hPD8/vV+xOkqEQ\nbMnZwoJN37B5VxZeYQpeQQrBgkQ3jVMwBg0mEetLJN6XSIy4ERSLQ8WUeEWE1MOHD58HmpdLYSiX\nAi+X/MQ8YuJ9xCbHEx9XiE9cMqxBDy0O4nkeXlDxQkowfIMjGPIhPj8SCCABP6B4wRBeKASqCH58\n6kPEh98fwB8TwBcI4A+F8JWU4CsuJuh5lKAU+cATdXdfCP9LFB/i8wE+AgoBVQKehydKEKXEr3ji\noRLCk2L3DzVciVWNwYeUndDcCaUYJR/xBSk9EaKCqh9PA3ieHxDUE7ePar8BB6V6F1cArrs6gYIC\nl8TFxLi7HBdc4JKwPn3cdyomBq65xk1lDbgv/W9/C8Bru9dRECyA5j2q7DuyCMsuX+bm252Aa4KS\nlgbAf/4D553nvuvRiERUdAGSk5F33nYV5vPP59KUFPqt/ZxhHYYR2LQFHnsMzrq7vKILbjqP995z\nzVKiVHTBDYyzfTvExg4CBnEC8ONV7rOLwKS72jDprvL1QyGX7LpWL0JRUYC0pkrarh9pvn056XFZ\ntPLvpE3CLpp0SGXi8+lM+/II8kikG6vod2QKvzqzkNwNu8jdlENBdjE7pYhVkkVWzG6Gd8pldPc4\nejdtjxQUUpi9k21ZO1hc0ppvizuzdFcbtuTEUxQsojhUhBcKkhbw01J8tARaiUdTCkj0cikM+Vlf\nEsOaYmFbEPK8EHkapFiCxMXkExebR0KggASfkOTzEY+fEEpeSMnzlGIP1FMXzzzwCfhEEHwk+4UU\nn59kn4+QxlLgxVEQiqVIfRQBhQglAD4P9bkLaB4+PE/wPB/xoQDJJQESinxIEIo0RBFKkSrF4lGM\ni2/hy394kYlxPYkrCUkj6vLt611cSUlIoE3T7ow46TsyTinksLZboMet7jZshJgY+POf97q7MpXz\nlRdfdLGqXTt3rk9Ohtaty/OVTp1chdjvL9+mNGf57DPXkOqrr1y+kJPjHsXF0KSJ0KSJunwlVWif\nnkL75ACdeiTSvoOUzRwULV+57z6Xq6xaBZmZ7mJ+ZL6SmuoeRUUuV1myxK3XvLkLWenp7jNG5itb\n87bx9cZv2ZC1Ha8gBa8wmVBhIhqMhVAsGkoiVhKJ8yURKwmAuHwlVExIQ+E8QiEvn8JQLvmhXAri\nCgjElxCXHEdcXDE+nw8UNOjhFQfRkMtVQkEIBT2CQQiF/ODz4wsE3AlCwQsFUS+EeooPHxJ++AMB\n/IEAPn8Mfi+EFJfgLykh6IW/0z4lRERrkXC+AuF8pyxfcbcDguIRDHiE8FDx8CToooL6QWNdxbZ0\nN4AQQiWIShEiIYTwRXzC+YoXwPNcFUPDOUzZv/x6ElfMwcOaMR9gVe6a4IJsaYK3v+vvi8irtqVJ\ndlycuxETqKvLHuagdDA1N6yscrPh0uRw9uzykVLNvrHYZuDgjiu14afkHwcqZ7HvtKkv7M5uw1dX\nUw/NBw4RkS4iEosb0OGtSuu8BVwY/n08MFNdzfwt4BwRiRORLsAhwLyfqdz7rMpdE9zz6k4C+7r+\nvoi8avvttzBlinu+bNn+79uYeqBBxJXSO5yld1rHj3fP+1Y/laTZC4tt5gBqEHGlNvyU/ONA5Sz2\nnTbG1JY6uT6mqgxyk7oAACAASURBVEERuRx4HzfS4VOqukRE7sCNevYWMBl4VkRWAjtxJxjC670M\nfA8EgctUdS+9NgxENiN0z8ePd32PYxrP+CTmINZQ4kp1yaH56Sy2mQOlocSVxsa+08aY2lInzZh/\nbnXZLMgYU1VjaBZkccWY+sXiijGmtjWGuHKwq6tmzMYYY4wxxhhjzAFjlV1jjDHGGGOMMY3OQdGM\nWUS2AWtquHoLYPsBLE5taAhlhIZRzoZQRmgY5dyXMnZS1RrM/Fh/WVypMw2hnA2hjNAwymlxpXqN\n7e9XlxpCORtCGaFhlPOgiisHu4OisrsvROSr+t42vyGUERpGORtCGaFhlLMhlLGuNIRj0xDKCA2j\nnA2hjNAwytkQylhXGsKxaQhlhIZRzoZQRmgY5WwIZTS1x5oxG2OMMcYYY4xpdKyya4wxxhhjjDGm\n0bHKblWP13UBaqAhlBEaRjkbQhmhYZSzIZSxrjSEY9MQyggNo5wNoYzQMMrZEMpYVxrCsWkIZYSG\nUc6GUEZoGOVsCGU0tcT67BpjjDHGGGOMaXTszq4xxhhjjDHGmEbHKrvGGGOMMcYYYxodq+yGicjJ\nIrJcRFaKyI11XZ7qiEimiHwnIt+IyFd1XZ5SIvKUiGwVkcURy5qJyAwRWRH+mVYPy5ghIhvCx/Mb\nETm1jsvYQUQ+FpGlIrJERK4KL69vx7K6ctar41nXLK7sH4srtVZGiyuNiMWV/WNxpdbKaHHFNAjW\nZxcQET/wA3AisB6YD/xKVb+v04JFISKZwBGqWq8m7BaREUAu8Iyq9gsv+wewU1XvDZ+Q01T1hnpW\nxgwgV1Xvr6tyRRKRNkAbVV0oIinAAmAscBH161hWV86zqEfHsy5ZXNl/Fldqh8WVxsPiyv6zuFI7\nLK6YhsLu7DpDgJWqulpVi4EXgTPquEwNiqp+CuystPgM4H/h3/+HCy51ppoy1iuquklVF4Z/zwGW\nAu2of8eyunKachZX9pPFldphcaVRsbiynyyu1A6LK6ahsMqu0w5YF/F8PfX3i6DAByKyQEQuqevC\n7EW6qm4CF2yAVnVcnupcLiKLws2G6rS5TSQR6QwcBnxJPT6WlcoJ9fR41gGLKwdGvf0uVFIvvwcW\nVxo8iysHRr39LlRSL78HFldMfWaVXUeiLKuv7buPUtXDgVOAy8JNXcxP9yjQDTgU2AT8s26L44hI\nMvAacLWqZtd1eaoTpZz18njWEYsrB696+T2wuNIoWFw5eNXL74HFFVPfWWXXWQ90iHjeHthYR2XZ\nI1XdGP65FXgd16SpvtoS7itR2mdiax2XpwpV3aKqIVX1gCeoB8dTRGJwAfl5VZ0aXlzvjmW0ctbH\n41mHLK4cGPXuu1BZffweWFxpNCyuHBj17rtQWX38HlhcMQ2BVXad+cAhItJFRGKBc4C36rhMVYhI\nUrhzPSKSBJwELN7zVnXqLeDC8O8XAm/WYVmiKg3IYWdSx8dTRASYDCxV1YkRL9WrY1ldOevb8axj\nFlcOjHr1XYimvn0PLK40KhZXDox69V2Ipr59DyyumIbCRmMOEzfk+AOAH3hKVe+q4yJVISJdcVdH\nAQLAC/WlnCIyBRgJtAC2ALcBbwAvAx2BtcAEVa2zAReqKeNIXBMWBTKBP5T2NakLInI08BnwHeCF\nF9+M619Sn45ldeX8FfXoeNY1iyv7x+JK7bC40rhYXNk/Fldqh8UV01BYZdcYY4wxxhhjTKNjzZiN\nMcYYY4wxxjQ6Vtk1xhhjjDHGGNPoWGXXGGOMMcYYY0yjY5VdY4wxxhhjjDGNjlV2jTHGGGOMMcY0\nOlbZNdUSkYtERKt5nFDX5QMQkYsjyhSs9Np6EXm6mu3urbx+Dd4rI+K9Mn96qY05eFlcqbKNxRVj\n9pPFlSrbWFwxJixQ1wUwDcIEYH2lZd/XRUH24HRg6wF+jyeB94AMoNcBfi9jGjuLK47FFWNqj8UV\nx+KKMWFW2TU18Y2qrqzpyiISp6pFB7JAUXytqpVPcLUqvP/1IrL9QL6PMQcJiytYXDGmlllcweKK\nMZGsGbPZLyJyQriZzFgReSocWDdEvH6YiEwTkV0iUiAin4vIUVH2c42IrBGRQhGZJyLDw816nvyZ\nPsdze2gCdfTPUQZjjGNxxRhT2yyuGHNwssquqQm/iAQiHv4o6zwMBIFzgd8BiMhg4AsgFbgYGA/s\nBj4SkUNLNxSRPwATgRnAGcBzwEtAk1oou1Qqe0BEAoBUWu82YFilx1wgF1hXC+UwxlRkccUYU9ss\nrhhjKrBmzKYmllV6/gVQ+erhbFW9pNKy+4HVwPGqWgIgIu/j+s/cAowPn4j+CryjqheHt3tfRHbg\nTiL764LwI5pQ6S+qugpYVfpcRG4EhgBjVXVNLZTDGFORxRVjTG2zuGKMqcAqu6YmzqTigA85UdZ5\nPfKJiCThTjC3Axq+OlnqI2Bc+PdOQFvgpkr7ewV4Zj/KXOrtcBkquxw4L9oGInImcDfwf6o6rRbK\nYIypyuKKMaa2WVwxxlRglV1TE4trMODDpkrPW+Cayd9O9ODthX+2Cf/cEvmiqhaLSNa+FjSKHar6\nVeWFIrI52soichjwLPCYqj5QC+9vjInO4ooxprZZXDHGVGCVXVNbtNLzrPCyScDze9iu9KSTHrlQ\nRGKBtForXQ2ISBtgGvA5cOXP+d7GmKgsrhhjapvFFWMOIlbZNQeEqmaLyGxgAK55TeWTS6k1wEbg\nLCo2A5rAzziAmogkAG8Bu4CzVHWfJnA3xhx4FleMMbXN4ooxjZtVds2BdA0wC3hPRJ4CNuOaCx0B\nqKrerKohEbkDeCw8bP8rQA/geqL3tTlQHsKd6C4E+ohUGPxwiar+nGUxxlTP4ooxprZZXDGmkbLK\nrjlgVHW+iAzBDZP/b9yQ/luABcBjEev9JzxAxNW4QRi+A84GXv4Zi9sLiAWmRHntGFxTIWNMHbO4\nYoypbRZXjGm8pPrWGsbULRFZD7wXMcR/tHUuBp4AOgPrVTVU3bq1UB4frqnS/4CjVLXzgXovY8yB\nYXHFGFPbLK4YU3/9bH0MjDnAMoGiA/wefwVKgF8f4PcxxtQPmVhcMcbUrkwsrhjzs7FmzKahewP4\nJvz7gW6m8DhuHjw48CcqY0zdsbhijKltFleMqQPWjNkYY4wxxhhjTKNjzZiNMcYYY4wxxjQ6Vtk1\nxhhjjDHGGNPoWGXXGGOMMcYYY0yjY5VdY4wxxhhjjDGNjlV2jTHGGGOMMcY0OlbZNcYYY4wxxhjT\n6Fhl1xhjjDHGGGNMo2OVXWOMMcYYY4wxjY5Vdo0xxhhjjDHGNDpW2TXGGGOMMcYY0+hYZdcYY4wx\nxhhjTKNjlV1jjDHGGGOMMY2OVXaNMcYYY4wxxjQ6Vtk1xhhjjDHGGNPoWGXXGGOMMcYYY0yjY5Vd\nY4wxxhhjjDGNjlV2jTHGGGOMMcY0OlbZNcYYY4wxxhjT6Fhl1xhjjDHGGGNMo2OVXWOMMcYYY4wx\njY5Vdg9CIvKkiKiITNzP/RwqIhki0qy2ymaMqf8shhhjKrO4UD0R6Rz+TF3rYvvwPlREMn7q9sY0\nVFbZPciISAIwIfz0XBEJ7MfuDgVuAxrNCckYs2cWQ4wxlVlc2KvOuM/0Uyur+7u9MQctq+wefM4E\nmgDTgVbAyXVbnANHROKqWe7fzxOxMQcziyF1HEOqK5cxdcjiguUWxtRLVtk9+FwIZAEXAQXABZVX\nEJGnRSQzyvJZIjIr/PtFwH/DL60IN49REekcfr2JiPxbRDaKSJGILBeRa0REKu2zpYg8IiLrwuut\nE5FnI08mInKyiMwRkQIR2S0ib4hIzyhl+1xExojI1yJSBPwp/JqKyF0icqOI/AgUA/2rO0AicruI\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J05ua6uiSCSHEFbuqG7tKKSel1Aal1Hx7nC/KP4qEzP3mgzR2haiWlFJBSqmlSqkEpdQ2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\nGBGCoUs8ouwG4qIuUOfXR3halKX8aT1c7VfjMvk1XKvq47J3OY7fvo/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TnP8OBuUdobHh\n2gZsTG1KfFGwrUtb0kRanpEiewP3Ym5onkMfAJBS8K+8ItWW33tPKp3OmZO/NL+iyPy4s2elQXzo\nkIy4qFVLeuKzofcgjG8/P8XVP60JGneLbtW66+qtqqioqOSPvr6cs8+elYI0NWvKihEVK8p9RiSL\nispziq6N3VlIkapZBWwvDUZuVWkTINhzc/fTXSgwEFxdufLgCgoKHjYeuhngE9LBtQNXw65mGYQZ\nYlLn8/asFMSVB1fYG7iXETFu6OlpoLvuHshsy9gyudlkzAwf8xS3aCEf4IOCaFaxGbNaz2Kjz0a8\nl3pTe3FtOvzaAad5TjRf2ZzoxGwrkcnJsH07okd31vv8RXvX9qUeEuhS3oUx9cew6uIqrsUGwpIl\ncPw4P37Zm1sJ95jTfk6mUFpeqEbui00Na5kF4hvuW2C7ezH3SE5LzgpjBrlIFRSUOxx2xw4Z7m9m\nBh07gru79Dxmw93SHYCbkTeLNN6AW+cAcLl+XxrVhw/LEHxXV6m0vHmzfDhKSJBhcG++KeeXn3/O\nN4TezsyO2na12Z3HvJqQksB2/+30rt67aIJYxaCxc2NM9E3YE7An12t7AvbQ2qV13p/F336TSn6L\nFklj/803C+/M01OqD965A2vWyLmpfXt5z/bsyfobBgXBn3/KaBYVFRWVZ4miyHlpzx44c0YuzH37\nrVQp/e67XBFDKirPCzo1doUQM4QQM/PagINAJV32V+q4u9M2AAKjb2V6OIpFQAC4uHA17Cqu5V0x\nNShAHbcEyCjnk/lQV6eOnNQKCWVOTE1k0alFbLi2gZCYEO7F3KPbb92wLWPLW3/flQ+76SqjJUpG\n6Y6D0gMzrcU0Qj8IZU3vNax7dR17X9/LV22/4kTwCbr+1pW45DjZ/sABiI7mTPta3Hp4WZjT6AAA\nIABJREFUi/41+5f8WJ+AKc2nYGZoxsTdE0nTphEeH87nhz+ng1sHNWzxJaeGjTR2fcJ8CmyXo+xQ\nBt7p9Y/PncvWMFAWge6aXhJKUWTJqf37pTJzOhnGblHzdv22rgKgyootcmErLwO2fXtZ4urAAWn4\nHjhQsAI4cgHuyO0jWZ/VdHbf3E1scmyJqTBnx1jfmLaubdnos5E0bVZNt4CoAAKiAmjnkk9OfPXq\nMm959mxpuBZlAcrQUIZ3X7ok6/AeOiRTQbp2lZE2//wj51UVFRWV0sTbWyrMX74MTZrIOr01a8KW\nLUWp+aii8kwo0dpQiqK4K4oyS1GUQGAv8HxYE7rCzY226TZusfN2ExPh3j1wceHKgyvUtK2pu/E9\nIZ52ntiVscsyds3NZW2h7A/NjxGTFEOXtV14d+e79FvfD4fvHHD8zpHw+HB2NF5EhUsBOg1hLpCa\nNaVRvX9/5iE7MzuG1B7CgFoDaOPShsnNJrPu1XUcDz7O2J1jZaPNm8HUlD/L3sFAz4Ce1Xo+m/EW\ngrWpNbNazWLnjZ30+qMXjZY3IjY5lm/afVPaQ1MpYSqXq4yhxhCf8EKM3exlhzJ45RW5z75ItWOH\n3HfNVv+4a1cpMLJvX+ahDIGpIuXtJifjE3AShxRjLFoWkutepoxclGrf/oly+Du6dyRFm5IrlHnd\nlXVYmljSqnKrJx/nUzDEcwh3Y+7mGMfeADnX5ysAB3IO/fBDGdZdHExMYPp06endtEkavbdvy5xr\nFRUVlecFDw/5PbNjh0yX6dVL6oxculTaI1NRyUTnxq6iKBaKorylKMoRwA+YCkQBowEHXfdXqri7\nUyMM7JWy/BuQt2pnoQQFAZBc2Rn/SH9q2dTS4QCfDD1Fj3au7dhzcw9aoZUH69Yt0NgdvHEwh4IO\n8UuvXzg28hjfd/6eKc2msPf1vXgfuC4b9XxGxqOenvR+7NgBaWn5Nuvr0ZfJTSez6sIq/rm2Ff74\nA9G1C+uvb6KDWwfKm5TP99xnzbhG45jXcR7br28nJjmGA8MO4FXBq7SHpVLC6OvpU9WqauHGblQg\nCgqVLLIFy5QvL8OHs39ut2+XYctVqmQda9FCGpzbt2ceMjEwwbmsc9E8u5s24WOehIeV7gX4m1Vs\nhrG+Mf/c+CfzWFhcGJt8NzG09lAMNAY67zMvelTrQVmjsqy5tCbz2L+B/+Jg7kB16+olPwBTU/nw\n2Lx5/nm/KioqKqVN585SM2LRIrl/5RWZwnE3H70UFZVniE6M3XSl5S6KovwOhACLgcrAD+lN3hdC\nLBFC5Ja1fJGxtkYxN6dtoj37AvdlGYpFIVB6aK7b6ZOqTS0Vzy7IUOaw+DAuhqYL3NStKz0J4eG5\n2t56eIut17cytflUXvd6ncbOjRnbYCxftP2Chk4NYeNGaNSo+F6N4tCrlxRJOHGiwGaftPyE6tbV\neXPTCK4rkczqbEpQdBCDPAc9o4E+Oe83ep+To05y4X8XnqlomUrpUsO6RqE5u4EPA3Ewd8BI3yjn\nC97eWZ7diAgpctTjsbr3hobSw7p9e45ws6KWHxJLl+Bjq1CjWtPCGxcRY31jWlZqyT83s4zd1RdX\nk5yWzJt1nyAHVkeYGJjQt0ZfNlzbQHxKPKGxoez030l71/ZqfryKiopKdgwMpHqzvz+MGyfFCt3d\nZSWAvMrQqag8I57a2FUU5VvgLrAV6A5sAjoBFYFPgZf3iUBRZN5usCFh8WFcup87bMM/wr9g0ZeA\nAACumMYCUNOmdIzdti5tAThw64A8kFf+XzqrL65GQWHkKyNzXygwUJ7Tu3cJjTQfOneWE+3mzQU2\nM9Y3Zk3vNcTFR1PnHYUZt1czvM5wBtYa+IwGWjTqO9bPLDOk8t+ghnUNAqIC8q0zC4/V2M1O3bpy\nTomKkqUiUlLyLnvTrRsEB0uRkXSKVH4oMpLgM/uJNRDUKCFBvd7Ve+MX4ccmn00IIVh2bhlNnJs8\n8wXB171eJzY5lnE7xzF2x1iS05L5uNnHz3QMKioqKi8M5ctLwSo/P+jbV5YpcnWFzz+HRy+Xz0vl\nxUAXnt0JgC2wA6gohBgshNgthNACL3+WupsbXS7EYaBnkKNWbUhMCF1/60rVRVVp9HOj/Et6BASA\nsTFXk++iUTRUs672jAaeE8eyjriWd+XQ7UPyQEb+32PGrlZoWXVhFW1c2lCpXB56Y/PmZcnUP0vK\nloU2baSxW4g4Qr0IIy4sSqWpkTv9PPqxtNtS1Uuj8txQ3bo6WqHFPyJ/wzNHjd3sZCxSHT0Kq1ZJ\nsbnatXO3e/VVGSK7dGnmoSqWVQiPDyciPiJ3+8c5cYJrNvLHklKPH/nKSLzsvBi7cyxjdozBL8KP\nt+q+VSJ9FUSLSi34uNnHLD+/nL98/uLTlp+W2jytoqKi8sLg4iJF+s6fl6kYn3wia69//jnExJT2\n6FT+Q+jC2F0BxABdAT9FURYpitJAB9d9MXB3x9b3Dv09+rHqwipikmLQCi1DNw3lwK0DTGg0gaiE\nKKbsnZL3+X5+UKUKV8Kv4m7pjrG+8bMdfzZaVmrJ4aDDMhy7XDm5EveYIvPhoMMEPgxkeJ3huS8Q\nEiIfnocNk/XXnjW9esGNG3D1av5tkpPhzTdxpix73j7Gn/3+fGb5fyqlj6Io/RRFuaooilZRlHqP\nvfaxoig3FEXxUxSlEMWlkiNTkTmfvN3ktGSCHwXnbew2agQODlk1EYcPz7sTCwsYOFCWyYmW5bgy\nQuXzq2+bg6NH8bFVcoxX1xhoDFjafSkhMSH8dOYnJjSawJDaQ0qkr4JQFIUv237Jgk4LeK3ma0xq\nMumZj0FFRUXlhcXLS5amO3Mmy+itWhVWrgRtMdL/VFSKyFMbu0KIUUAFYAhwFngbOK4oig/wES+7\nd9fNDVJSeLdiX2KSY1h6dimzj8xmb+Be5necz9yOc3mv4XssPbuU03dP5z7fzw+qVePqg6ullq+b\nQYtKLYhIiMgqe+Ltncuzu8l3E8b6xvSunkeY8uzZkJoKH5dSiF+fPmBsLOu+5cfHH8PJk7B8OVhb\nP7uxqTwvXAH6AIeyH1QUxQMYANREpmH8qChKyRZyzYdqVtVQUPLN270dfRuByDuM2dxc5q27ucnP\nwqACctHfeQfi4+XKO9DQsSFmhmZPJrZ37Bg+1a2wMrHCxtTmSd5WsWjg2IC1fdayY9AO5nacW+K1\ndQvivYbv8Xvf39XFMRUVFZXi4O0tSxOdOCE9vCNHQv36cORIaY9M5SVHJwJVQohEIcRvQoiOgDMw\nBUgDJiNzdr9WFGWIoiil57YsKdzcAGj4qCz1Heozcc9EpuybQreq3RhVdxQAM1vNxNzInCVnl+Q8\nNzkZAgJ4VK0y/pH+1LGr86xHn4MWlVoAcCgo3Q7Inv+Xzq4bu2hVuRVlDMtknSgEfPUVLFggPUnp\n9+SZY2sLo0fLh/fr13O+Fh8vJ9bvvpNt+vUrnTGqlCpCCB8hhF8eL/UEfhdCJAkhAoEbQKlEqJgY\nmFC5XOV8Pbt51tjNjrOzfJjw9QWbAgxRb2/5oDF1Ksybh8HtYFo6Ny+8jFpKCpw6xTUHQ2rY1Cjx\nFICBngPpXKVzifahoqKiovKMaNgQjh2DtWvhwQPp7X3tNVlqTUWlBNB56SEhRIgQYrYQohbQEPgR\nqAKsRio1v1y4u8v9jRss7raYWa1msem1TWzotyHzIdDcyJwe1XqwyXcTKWkpWecGBkJaGuedpafA\n28H7WY8+By7lXHA0d8zK223YUO4Pyd8DowLxi/Cjk1unrJP+/htatYIpU6QX6YcfKFU+/FB6tKZO\nzQqP8fOT4Z2rVsnwmYULS3WIKs8ljkD2b9rg9GOlQnXr6lkRFo+RZ43dxzExgUp55NQ/zu+/Q5Mm\nMGECuLrS7tdjXI+4zu3o2/mfc+kSIj4eH+MYaliXTAizioqKispLjKLIZ0Y/P5gxA7ZulTV758+X\nEYIqKjpE58ZudoQQp4UQY5H1dfsCT5AM9oLh6AhGRnDzJnXt6/JJy0/oVb1XrpIgfWv0JTIhMkvt\nGOSHHDhrEQeAt33pGruKotCiUgsO3DqAEAKaNpXCT9u2AdKrC9DJvZP05k6bJmvpBgVJA3LNGnkv\nShM7O5g0CTZskEb48OHSgxUSAjt3wqxZoCm9UEiVkkdRlH8VRbmSx1ZQ4ee83JO5UjDSa4ifURTl\nTFhYmO4G/Rg1rGvgF+FHmjZ33ejAqEAM9AxwNNeBLe7qKutTHzsG339Pu/Myf3dvQAHe3WPHuGQH\nEWkxNHD878gzqKioqKjoGFNTmD5daq20aAHjx0ODBrn0YlRUnoYSNXYzEEKkCCE2CiF6PYv+nil6\nevKB8UbB9Sk7uHXAzNCMDdc2ZB1MN3bPEYKjuSN2ZnYlOdInooNbB0JjQ2UZJUND6NhR1uPUatl1\ncxcu5VyoalUVPv0UvvhCFg2/cQPefVfei+eB6dOlF/fSJel57t1bqgF2LDXNIZVniBCinRCiVh7b\nlgJOC0amYGTgBNzL49pLhRD1hBD1bAoKEX5KatjUIDE1MU8Pa+DDQCqVq6S7/FVFgcaNYexYatbv\ngl28HjMPzODDPR+y4vwKrjy4krP9iRNsqW+OgkL3qt11MwYVFRUVlf8uLi7SsbJ+PYSGysjCGTNk\n2oyKylPynFgnLzhubnCzgFq6yDy8blW7scl3E6na9BANPz+wteVsxOVSD2HOoJO7DFHe4b9DHuje\nHUJCSDx9nL0Be+nk3gllzx4pHT9yJCxeLEsNPU8oilSEDguT+SBr1oCTU2mPSuX55m9ggKIoRoqi\nuCBTL06V1mAywoPzytsNfJhP2SEdoIyfwM+btFRKMmbeiXm88fcb1Flch903d2c1On+eLR56NHJq\n9Fws0KmoqKiovAQoiqzLe/WqDHGeOVOmoBVUYUNF5QlQjV1d4O4ujd1C6rv2rdGXsPgwDgcdlgf8\n/IjxcMMv3K/UQ5gzqGBWAW97b3bcSDd2O3cGPT127FxIXEocvexby9DgGjVg0aLnx5ubFwYGz58h\nrlKqKIrSW1GUYKAxsF1RlH8AhBBXgT+Ba8AuYIwQIncM8TOiunV1gDzzdvOtsasL2rShq2FNDu6s\nQNyUOK6PvU5N25r0/bMvF0MvQnw8t0N8OWcaTc9qBUWFq6ioqKioFIPy5WH1avjrLylaVbcuzJkD\naaX2lazygvMcWyovEG5uEBcH9+8X2Kxzlc6YGphmhTJfv86FGpYIxHNj7AJ0qdKFY3eOEZUQJcvz\nNGnCr7f+xs7QkjZvz4aICKmiZ2JS2kNVUSkSQohNQggnIYSREMIuXUE+47UvhBBuQohqQoidpTlO\nK1NZ0udxz25scixh8WEFi1M9DYoiw/1PnsQwVVDFqgrbB22nrFFZWv/Smv0HV7HYWy7q9ar+8mWl\nqKioqKg8J/TpA1euQJcuUnzUy0uGOasCVipFRDV2dUE2ReaCMDUwpUuVLmz03UhaZAQ8eMAZJ6mL\n87yEMYM0drVCmxm6GPXt52yvmMjAg5HoX7gkV9teeaWUR6mi8nJTw6ZGrlq7tx7eAgooO6QLWrSA\npCQ4LeuCO5V14vCIw1ibWtPm1Bi+ag7NbOtRzbpayY1BRUWlQHbf3F2warqKysuArS1s3Jhl5Pbv\nDxUrwsSJcPSo6u1VeSJUY1cXeHrK/fnzhTbt59GP0NhQjh5cgwBW6l/B09aTCmYVSnaMRaC+Q33s\nzez59vi3pGpT+cvAn2QNDHbqLAWfunUr7SGqqLz01LCugU+4j1RGT8c/wh8A1/KuJddxs2Zyf/hw\n5iGX8i4cHXmUr2Ma8c9fpux782jJ9a+iolIgado0hmwcQqX5lWi2ohmn7paavMATk5CSQLffupGQ\nklCk155XXsQxv7Bkz+XdtAnq1ZMVQJo1AwcHePttuHy5tEep8hyjGru6wNFRfuBOniy0aZcqXTDW\nN2bFpV/YVQUuJ9xiYpOJz2CQT45GT8O8jvM4c+8Mb219i8n/TsbDxgPvZduhU6fCL6CiovLU1LCu\nQWRCJGHxWSWOztw7g76ePrVsa5Vcx1ZWst5hNmMXwKaMDR8dU+hgWR8DfcOS619FRaVANHoaTow6\nwZdtviQoOogmPzfhs4OfZYlfFpFnYbj9c/Mftvtvzyl29wSvPa+8iGN+4dFooFcv6XQJD5d14tu0\nkfm9tWtD+/aZ1UNUVLKjGru6okEDOFX46qqZoRn/8/4fv3CBwf00OJo7MqDWgGcwwKLRv2Z/elbr\nycoLK7EytWLLgC0oSl6lSFVUVEqCDJGqa2HXMo+dvHuS2na1MTEo4Xz55s1zh4ilpclyXnXqlGzf\nKioqheJa3pWPm3/M5Xcu079mfz498CmtVrWSZQOLSEkZblEJUZwLOce5kHMsPrMYgJ/O/MS5kHMc\nuHWAg7cO5vnauZBzPEx8qNOx6IKC3s+TjPlZLCoUp48X0ktdtiy89hqsWwfBwfDVV+DjIyMPPTzg\np5+klo6KCvDCSdUqijIH6A4kAzeBEUKI0p8VGzaEzZshMhIsLQts+l3bb9D+9CPf101hWuMJGGqe\nPy+Joigs676Meg71GF1/NJYmBb8nFRUV3VLPoR4KCgdvHaRV5VZohZbT904z2HNwyXfeogUsWSKN\n24z8/Bs35MODauyqqDw3lDMux2+v/ka3qt0YvX00Xou9aOzUGC87L+zM7DDRN8G2jC3OFs7UtquN\nbRlbQBpugQ8DAXIYbs4Wsty4a3lXyhmXK7T/pNQk/CL8CH4UzN1Hdwl+FExobCihcaGcvXeWuzF3\nc7T/5+Y//HPzn8zfFZTMhfQ9AXvYE7AHrdDSp3ofPmz6IVWsqjwXzx9aoWXmwZksOLkAjaJBEQZw\nuzF7OUCDgAakiTRmtpzJp60+zfca2RcVelYvGTX74vTxpOckpCTQb30/1vdbX+ILrkXqy9ISJk+G\nDz6ADRtg3jwYPRqmToW33oKxY9Xyk/9xXjhjF9gDfCyESFUUZTbwMfBRKY9JenZBirp07FhgU73L\nV1jwdwojen+JV6P3n8HgiodNGRumtZhW2sNQUflPYmVqRQPHBuy6uYvprabjF+7Ho6RHNHBsUPKd\nt2wp93v2ZBm7R47Iff36Jd+/ispLhKIonYAFgAZYLoT4Wtd9DPIcRCf3Tvx87mfWX1vPn9f+JDIh\nMlc7ezN76lSoQ2xyLIdvH0Zf0UejpwHgwK0DNFzWkFSRysTGE5ndfjZ6Ss4AwDRtGudCzrE3cC/7\nAvdx5PYRElKzPIIKCjZlbKhgVoFatrVwNHfkbMhZ0rJVctMoGrwdvEnTpnEh9ELma1qhlcYvCht9\nN7LRdyMAViZWuFu641reFdfyrtS0qUkDxwa4lnctdsSZEIJUbSrxKfEEPgzkesR1rkdcxz/Sn8Co\nQOJT4klITSAxNZH4lHiiEqJISkuS90CkQaoGjB+RmqKAgRz/b1d+Q09Pj8GegzMV83W1qFAQxemj\nOOc8C2P9qfoyMICBA2HAADh2TBq9c+bA3LkwZIg0iKupwor/RRRRSG3Y5xlFUXoDfYUQBbo66tWr\nJ86cOVOyg3n0CMqVgxkz4NP8V/YAmVg/bpysH6auNqn8B1EU5awQol5pj+NpeBbzyswDM5l5cCZh\nk8LYdn0bw7cM5+roq3jYeJRov4D04FpYwMGD8vfXXpMGb3CwFAxRUXnOeB7nFUVRNMB1oD0QDJwG\nBgohruXVXpfzilZoSUhJ4EHcAwKiArh4/yIXQi9w8f5FroVdKzTH11BjiEs5F+zN7TE1MCU8Ppzr\nEdczw3Vr2tSkrUtbGjs3ppJFJZzKOlHBrAIGGoMc1+m3vh9/XfsLgUBBoa9HX/7s92e+r63pvYbA\nh4H4R/hnGqEBDwMIiAog6GFQpnFsZSIXBDO2OhXqYKQxIiIhAt9wX/zC/fCL8ON6xHVCY0OJS4kj\nLjmOhNQEktOS83zPTmWdcCnngrmROSb6JhjrG2NqYIqFkQVOJtUwT6rBL2d+59DyrnCzI7j9Q7NR\nf9OiqhcHIn/j2N1DALiVd6O6dXUCogLwCfdBDz0URSFNpKFRNAgEWqGlk1snhtQegomB7KuwTV9P\nnzvRd/CPlPfGP8KfnTd2cjPqZr5/RzNDM6xMrDDWN8ZI3wgjjRH34+5zO/p2jnHp6+kjhCBNpNGz\nak+GvzIcI40R8anxmOqbMvvobA4GHaR15dZ80/4b9BQ9nRjrGWQY4EmpSUzbN419t/bRqlIrprWc\nhrHGmBo2NYru5b91Sxq9y5ZBYqIUuho/Hho1euLvsedxXlEpGi+6sbsV+EMI8WtB7Z6JsQtQsya4\nuMC2bQW369sXzpyRH0IVlf8gL8OXx7OYV04Gn6TRz41Y9+o6DgcdZs2lNUR9FJXpiSlRpk6F2bMh\nLEzmR9nYQM+esHJlyfetolIMnsd5RVGUxsCMjJreiqJ8DCCE+Cqv9k86r/TuLUveGxvLkvfZ93kd\ne3yvMUwmThvBvDNfcSzkX9BPAkVLs4rNGe41nHsx9wh+FEzQoyAi4yOJT42nvHF5nMydaOTUiMbO\njbE2tSEtjcxNq836WQjQ04NUbQotf2lOikjCzdKFm1E3MNTX5/RbpwBB/WX1SdYm4W7pzo1Ifww1\nhpx/+xz6evo5bJGMn1O1KfhH+nPp/kXOh57n4v0LXI+4LlXrhQIoOfZWJjZULueCrakdJvqmmOiX\nwUjPGAONIfqKAYYaI+xMnHAwrYSdiRP6mJCSQp7bxo2wdSugpIBeGqQZgyYRtBoQBvTqBc07hnM6\n5ASBj/wJjQtGKKnEpEYRlRQOSqo8T9GCokWjUUgjCZT0Yxmv8eTP5aYGZahUrhICgX+4P2kiawFD\no+jjZe9FJYtKpGpTSU5LJik1iRRtMslpKdyNCeZezL0i9fc4DmaO1HWoi72ZPfbm9hhqDElMTSQx\nNZHY5FiiE6OJToomJimGVJFKWpqWNJGGVmhJ1aai1QpSRSqp2lRCY0KJS348zzbbP4FQ0NcYYKzJ\nMNqNMw14UwNTjDUmmBiYYKKfsZlmLlaYJKdhfPICxsdOYRqbiLGdE/3XfIF5zRqFvsfncV5RKRrP\nZRizoij/AnnV4pkqhNiS3mYqkAqszecabwFvAVSsWLGERvoYjRrJWmChoVAhn1JC585J6fQxY/7f\n3t1HyVXfdRx/f3azCSUEaEkVCgkBA1bE5JCEh5CKVYrlQAv2BHtQJEFKekgPqE0tUkUFPKQ9Le1B\nbC2HGmhJgVLSgpEmRrFqVQgSaR4ISE0A2TQ8JzxJsruz8/WPezdsZje7M7OTO3fufF7n3DMP9+k7\nv+R+Zn/3abKpycxa1pz3zeGwdx3G8o3L2bpjKycfeXI2HV1IbvSxdCmsWZPsxNu5c9RLNMxsiCOB\n7kGvtwGnjnWhBx0Er70Gb76Z7I/atSs5cDX4sa9vpCWMB44Abt7r3X9Ph5F8p6ZKu4C1QHJ4G2AX\ncOJNA+PXA/DUoHHv/8poyzshHX5r1LW/mg4NFV3Qnx697j9gz9v33w/33z8ZqO7nGRvxC7FvA0+O\nsPzH0mF/2Z4OWSkBb6VD7X7nnafb4aToZlZDqrK8y2VnNyI+NNJ4SQtJ0uTM2Meh6Yi4FbgVkj2l\nDS9yOJ/9LNx5J1x5ZdLpLZdhw4bkG+nYY+HAA2HRouQIyXXXZVKSmbWuzo5OPjz9w9y16S4AFs9Z\nnN3KTzkFJk9Ofsrh+OOTQysfGjGazWyo4c6V3Otvknp2zi9fPvo0/f1Jx3dgqOwQP7H9GT79g6u5\nfOYSZk4+lUd/+ijLfryMa864hqMOru4Sq87OvYeOjuRRSo7u9vcHff0lOtVFuZz8WdTXX0KR7LQr\nlQdOn02Wl0zbyeBmGxg30qM0+tDRMfz7XV3VDx0dwaJPlln1g3d2Op77kX5u+XoH5bIolaBUStp+\n4HlPb4lfvf0s+kplph1yDM/s7Ga8DuC+j6+E6NxzRHzgsR6lcokF9y2gr9zHlIOn0P1GN10dXSz/\n2PJhd5BGJPMsvG9hOs9RdL+xja6OLu742B1D5rnxoRtZu20tyX9dMfeouXzm9M/sGd9f7mfHrh30\nl/uZ0JWcKj2hcwId6hxytvBor7/00Bd5uPvhPes6fepcrpp3VVXzVr4ulfvoKe1md38Pu/p20dO/\nm57+3ezu62H6MTOGNqQVU0S01ACcDTwBvLfaeWbPnh2ZWbo0AiJmzYo49NDkeeXw3e9mV49ZDgHr\nIgd5MpYhq1zpfr077t50d2x/Y3sm69vLxRdHdHVFHHxwxJw52a/frAZ5zBVgLrBm0OvPkdxks+l/\nr5TL5egp9ez1Xk+pJ8rlcmY1tJre3oiJEyPGjYuYMSN5nDgxoq9v3/NsfGFjTFo6KVZsXhEREfdu\nvjcmLZ0Um17c1LC66llHtfP0lnpj4g0TY9z142LG12fEuOvHxcQbJkZf/wgfuk5ZrqtaecwVD7UN\nLXfNrqQtwATeOTNlbURcPtI8mV2zC8l5QxddlFxMM3168nuVhx8OzzyT7EqdOhXOO883eLG2VoRr\nYDLNlWbZuhVuuin5CaJFi5I7WprlVB5zRdI4kjN4zwR+SnKDqt+OiM3DTd8WudLCNm2CefOSWxfM\nn5/80s2llyY3/z3xxOHniQj6yn17/cxkb38vXR1ddd9NuhHrqHaeTS9uYt5t87j9/NuZf8J8Vjyx\ngkv/9lIe+sRDnPgz+/jQdcpyXdXKY65YbVqus1sPf3mY5UsRvjycK2b5ktdckXQOcBPJTw/dFhE3\n7Gta50q+RSTHNMa/0z+ktzc5xbmoxzCy6Kw3Y13VymuuWPVyec2umZmZWRFExCpgVbPrsLGT9u7o\nwtDXRSNpr84nMOR1K67L2kfH6JOYmZmZmZmZtRZ3ds3MzMzMzKxw3Nk1MzMzMzOzwmmLG1RJehn4\n3yonnwy8sh/LaQTXOHZ5rw+KXePREfHeRheTJedKU+S9xrzXB8Wu0bmSP65x7PIGXPqRAAAJaElE\nQVReHxS7xpbPlXbXFp3dWkhal/e7rrnGsct7feAai6QV2sk1jl3e6wPXWCSt0E6ucezyXh+4Rss3\nn8ZsZmZmZmZmhePOrpmZmZmZmRWOO7tD3drsAqrgGscu7/WBayySVmgn1zh2ea8PXGORtEI7ucax\ny3t94Botx3zNrpmZmZmZmRWOj+yamZmZmZlZ4bRtZ1fS2ZKekrRF0tXDjJ8g6Z50/COSpuWsvksk\nvSxpfTpclmV9aQ23SXpJ0uP7GC9JN6efYaOkWTmr74OSXh/Uhn+WZX1pDVMk/bOkJyVtlvT7w0zT\n7Haspsamt2UeOFcaUqNzZew1OlcKxLnSkBpznStV1tjU7cG5Yi0rItpuADqBrcCxwHhgA3BCxTSf\nAm5Jn18I3JOz+i4BvtrkdjwDmAU8vo/x5wCrAQGnAY/krL4PAg80uQ2PAGalzycBPxnm37rZ7VhN\njU1vy2YPzpWG1elcGXuNzpWCDM6VhtWZ61ypssambg/OFQ+tOrTrkd1TgC0R8XRE9ALfAc6vmOZ8\n4Fvp8xXAmZKUo/qaLiJ+BOwYYZLzgTsisRY4VNIR2VRXVX1NFxHPR8Rj6fM3gSeBIysma3Y7VlOj\nOVcawrkyds6VQnGuNEDecwXyny3OFWtV7drZPRLoHvR6G0M3hj3TREQJeB04LJPqqqsPYH56msgK\nSVOyKa0m1X6OZporaYOk1ZJ+sZmFpKeenQQ8UjEqN+04Qo2Qo7ZsEudKNnKzPYwgN9uCc6XlOVey\nkZvtYRS52B6cK9ZK2rWzO9wez8rbUlczzf5Szbr/DpgWETOAB3lnr26eNLMNq/EYcHREzAT+Cri/\nWYVIOgj4HvAHEfFG5ehhZsm8HUepMTdt2UTOlWzkYnsYQW62BedKIThXspGL7WEUudgenCvWatq1\ns7sNGLxn8Shg+76mkTQOOITsTi8Ztb6IeDUietKX3wBmZ1RbLapp56aJiDci4q30+SqgS9LkrOuQ\n1EUSyndGxPeHmaTp7ThajXlpyyZzrmSj6dvDSPKyLThXCsO5ko2mbw+jycP24FyxVtSund1HgeMk\nHSNpPMkNHVZWTLMSWJg+vwD4YURktXdq1PoqroE4j+S6hLxZCSxI7853GvB6RDzf7KIGSDp84Lom\nSaeQbA+vZlyDgGXAkxHxlX1M1tR2rKbGPLRlDjhXsuFcGb0G50pxOFeyketcgeZvD84Va1Xjml1A\nM0RESdIVwBqSOwneFhGbJV0PrIuIlSQby3JJW0j2kF6Ys/p+T9J5QCmt75Ks6hsg6W6Su9pNlrQN\n+HOgK/0MtwCrSO7MtwV4G/jdnNV3AbBYUgnYBVyY4R8IA+YBFwObJK1P3/tjYOqgOpvajlXWmIe2\nbCrnSmM4VxrCuVIQzpXGyHuuVFljs7cH54q1JPnf18zMzMzMzIqmXU9jNjMzMzMzswJzZ9fMzMzM\nzMwKx51dMzMzMzMzKxx3ds3MzMzMzKxw3Nk1MzMzMzOzwnFnt81IiiqGZ9NpvznwvNkkXSsp81uH\nS3p2ULtcW8N8H6ho0+n7sUyzpnKu1Lxe54rZKJwrNa/XuWI2jLb8nd02N7fi9X3ABuDaQe/1pI9/\nAfxlBjXl3SqStthWwzwbSNr6XOCa/VGUWY44V2rnXDEbmXOlds4Vswru7LaZiFg7+LWkHuCVyvfT\nabdmVli+vTxc+4wkIt4E1kp6/36qySw3nCt1ca6YjcC5UhfnilkFn8Zs+1R5WpCkaekpLpdL+ryk\nFyS9Kenbkg6UNF3SGklvSdoiaeEwy5wpaaWknZJ2SfoPSb9cZ31XSHpY0g5Jr0laK+ncYaY7VtIq\nSW9LeknSlyV9Mv0s0+pc9/GS7kuXt1vSc5LuleQdSGYjcK6MuG7nilkdnCsjrtu5Ym3N/9GtHp8D\n/gVYCJwAfBEoAycB3wBuBBYDt0taFxGbASTNAv4N+DGwCHgbuBx4UNLpEfFfNdYxDfgb4FmS/8sf\nBR6QdE5ErE7XOR74R+AA4FPAS8BlwAV1fO7BHgBeI/mcrwBHAufgHUhm9XKuOFfMGs254lyxNufO\nrtVja0QM7AVdk+7pvBi4OCK+DSBpHXAeSUhvTqf9EvAc8GsR0ZtOtwZ4HPhT4DdqKSIi/nDguaQO\n4J+A40m+kFanoy4BjgVOjYj/TKddDawHptayvkHrmgwcB5wfESsHjbqrnuWZGeBcca6YNZ5zxbli\nbc57daweqyte/3f6uGbgjYjYSbJXcgqApHcBvwLcC5QljUtPoRHwIHBGrUVImi3pAUkvAiWgDzgL\n+PlBk50GPDfwxZHWFsD3al3fIK8CTwNfkLRI0nFjWJaZJZwrzhWzRnOuOFeszbmza/XYWfG6d4T3\nD0ifvwfoJNkj2lcxXAG8O93bWRVJU0j2jL4HuBI4HTgZ+PtB6wQ4guRLrNKL1a6rUvrlcxawDvg8\n8BNJT0taXO8yzcy5gnPFrNGcK84Va3M+jdmy8hrJdTJfA+4YboKIKNewvLOBQ4CPR8SeW+xLOrBi\nuudJrtOp9LM1rGuIiHgaWCBJwEySL8C/lvTswPU3ZrbfOVfMrNGcK2YF4iO7lomI+D+Smz3MBB6L\niHWVQ42LHPiS6Bt4Q9LxwLyK6dYCUyWdMmg6AfNr/hDDiMR6YEn61omNWK6Zjc65YmaN5lwxKxYf\n2bUsLQF+RHKTiGUkezEnA7OAzoi4uoZlPUhy3csdkr5McvrPdSQ3lBi8E+ebwB8B35f0J8DLJHc3\nfHc6vpa9swBImkHy4/X3AFtITne6JK3nh7Uuz8zGxLliZo3mXDErCB/ZtcxExGMk16m8CtwM/ANJ\nCP8SyZdKLcvaDFwEHA2sBK4Crq5cTnoXxV8HNgK3AN8CuklOTwJ4vY6P8gLJl9SSdN13A+8DPlLH\nzxGY2Rg4V8ys0ZwrZsWh5Np1s/Yi6QHgFyLi50aZ7lngX4FPAOVartNJ7964AFgGHBcRW+qv2Mzy\nzrliZo3mXDEbG5/GbIUnaQnwFvA/wCTgN4FzSX5gvRoL0uE64Noq1/kBkmt+zKyAnCtm1mjOFbPG\nc2fX2kEP8GmSH2XvBJ4CLouIZVXM+1FgQvp8ew3rXE9yCtSA7hrmNbP8c66YWaM5V8wazKcxm5mZ\nmZmZWeH4BlVmZmZmZmZWOO7smpmZmZmZWeG4s2tmZmZmZmaF486umZmZmZmZFY47u2ZmZmZmZlY4\n7uyamZmZmZlZ4fw/mf4HWL3CVR0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f05d0a35940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = ['x-component', 'y-component', 'z-component']\n",
    "colors = ['r', 'g', 'b']\n",
    "suptitle = \"Different signals for the activity: {}\"\n",
    " \n",
    "xlabels = ['Time [sec]', 'Freq [Hz]', 'Freq [Hz]', 'Time lag [s]']\n",
    "ylabel = 'Amplitude'\n",
    "axtitles = [['Acceleration', 'Gyro', 'Total acceleration'],\n",
    "            ['FFT acc', 'FFT gyro', 'FFT total acc'],\n",
    "            ['PSD acc', 'PSD gyro', 'PSD total acc'],\n",
    "            ['Autocorr acc', 'Autocorr gyro', 'Autocorr total acc']\n",
    "           ]\n",
    " \n",
    "list_functions = [get_values, get_fft_values, get_psd_values, get_autocorr_values]\n",
    "\n",
    "f, axarr = plt.subplots(nrows=4, ncols=3, figsize=(12,12))\n",
    "f.suptitle(suptitle.format(activity_name), fontsize=16)\n",
    " \n",
    "for row_no in range(0,4):\n",
    "    for comp_no in range(0,9):\n",
    "        col_no = comp_no // 3\n",
    "        plot_no = comp_no % 3\n",
    "        color = colors[plot_no]\n",
    "        label = labels[plot_no]\n",
    " \n",
    "        axtitle  = axtitles[row_no][col_no]\n",
    "        xlabel = xlabels[row_no]\n",
    "        value_retriever = list_functions[row_no]\n",
    " \n",
    "        ax = axarr[row_no, col_no]\n",
    "        ax.set_title(axtitle, fontsize=16)\n",
    "        ax.set_xlabel(xlabel, fontsize=16)\n",
    "        if col_no == 0:\n",
    "            ax.set_ylabel(ylabel, fontsize=16)\n",
    " \n",
    "        signal_component = signals[:, comp_no]\n",
    "        x_values, y_values = value_retriever(signal_component, T, N, f_s)\n",
    "        ax.plot(x_values, y_values, linestyle='-', color=color, label=label)\n",
    "        if row_no > 0:\n",
    "            max_peak_height = 0.1 * np.nanmax(y_values)\n",
    "            indices_peaks = detect_peaks(y_values, mph=max_peak_height)\n",
    "            ax.scatter(x_values[indices_peaks], y_values[indices_peaks], c=color, marker='*', s=60)\n",
    "        if col_no == 2:\n",
    "            ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))            \n",
    "plt.tight_layout()\n",
    "plt.subplots_adjust(top=0.90, hspace=0.6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Extract Features from the signals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ataspinar/anaconda3/lib/python3.6/site-packages/scipy/signal/spectral.py:1633: UserWarning: nperseg = 256 is greater than input length  = 128, using nperseg = 128\n",
      "  .format(nperseg, input_length))\n"
     ]
    }
   ],
   "source": [
    "X_train, Y_train = extract_features_labels(train_signals, train_labels, T, N, f_s, denominator)\n",
    "X_test, Y_test = extract_features_labels(test_signals, test_labels, T, N, f_s, denominator)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. Classification of the signals"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.1 Try classification with Random Forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy on training set is : 1.0\n",
      "Accuracy on test set is : 0.8815744825246012\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          1       0.93      0.98      0.96       496\n",
      "          2       0.93      0.96      0.94       471\n",
      "          3       0.96      0.88      0.92       420\n",
      "          4       0.80      0.73      0.76       491\n",
      "          5       0.78      0.93      0.85       532\n",
      "          6       0.91      0.82      0.86       537\n",
      "\n",
      "avg / total       0.88      0.88      0.88      2947\n",
      "\n"
     ]
    }
   ],
   "source": [
    "clf = RandomForestClassifier(n_estimators=1000)\n",
    "clf.fit(X_train, Y_train)\n",
    "print(\"Accuracy on training set is : {}\".format(clf.score(X_train, Y_train)))\n",
    "print(\"Accuracy on test set is : {}\".format(clf.score(X_test, Y_test)))\n",
    "Y_test_pred = clf.predict(X_test)\n",
    "print(classification_report(Y_test, Y_test_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.2 Try out several classifiers (to see which one initially scores best)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trained Gradient Boosting Classifier in 87.67 s\n",
      "trained Random Forest in 0.52 s\n",
      "trained Logistic Regression in 17.53 s\n",
      "trained Nearest Neighbors in 0.62 s\n",
      "trained Decision Tree in 1.45 s\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>classifier</th>\n",
       "      <th>train_score</th>\n",
       "      <th>test_score</th>\n",
       "      <th>train_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Gradient Boosting Classifier</td>\n",
       "      <td>0.990751</td>\n",
       "      <td>0.899559</td>\n",
       "      <td>87.668457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Random Forest</td>\n",
       "      <td>0.998096</td>\n",
       "      <td>0.857482</td>\n",
       "      <td>0.524725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Logistic Regression</td>\n",
       "      <td>0.882617</td>\n",
       "      <td>0.811673</td>\n",
       "      <td>17.526514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Decision Tree</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.787920</td>\n",
       "      <td>1.448587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Nearest Neighbors</td>\n",
       "      <td>0.854461</td>\n",
       "      <td>0.688497</td>\n",
       "      <td>0.622217</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     classifier  train_score  test_score  train_time\n",
       "0  Gradient Boosting Classifier     0.990751    0.899559   87.668457\n",
       "1                 Random Forest     0.998096    0.857482    0.524725\n",
       "2           Logistic Regression     0.882617    0.811673   17.526514\n",
       "4                 Decision Tree     1.000000    0.787920    1.448587\n",
       "3             Nearest Neighbors     0.854461    0.688497    0.622217"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#See https://github.com/taspinar/siml\n",
    "dict_results = batch_classify(X_train, Y_train, X_test, Y_test)\n",
    "display_dict_models(dict_results)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.3 Hyperparameter optimization of best classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "GDB_params = {\n",
    "    'n_estimators': [100, 200, 5000],\n",
    "    'learning_rate': [0.5, 0.1, 0.01, 0.001],\n",
    "    'criterion': ['friedman_mse', 'mse']\n",
    "}\n",
    "\n",
    "for n_est in GDB_params['n_estimators']:\n",
    "    for lr in GDB_params['learning_rate']:\n",
    "        for crit in GDB_params['criterion']:\n",
    "            clf = GradientBoostingClassifier(n_estimators=n_est, \n",
    "                                             learning_rate = lr,\n",
    "                                             criterion = crit)\n",
    "            clf.fit(X_train, Y_train)\n",
    "            train_score = clf.score(X_train, Y_train)\n",
    "            test_score = clf.score(X_test, Y_test)\n",
    "            print(\"For ({}, {}, {}) - train, test score: \\t {:.5f} \\t-\\t {:.5f}\".format(\n",
    "                n_est, lr, crit[:4], train_score, test_score)\n",
    "                 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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